Nuance Communications, Inc.

Patent Trials and Appeals Board

May 11, 2020

IPR2019-00210 (P.T.A.B. May. 11, 2020)

Trials@uspto.gov Paper 42
Tel: 571-272-7822 Entered: May 11, 2020

UNITED STATES PATENT AND TRADEMARK OFFICE

BEFORE THE PATENT TRIAL AND APPEAL BOARD

MMODAL LLC,
Petitioner,
v.
NUANCE COMMUNICATIONS, INC.,
Patent Owner.

IPR2019-00210
Patent 9,818,398 B2

Before KEN B. BARRETT, NEIL T. POWELL, and CHRISTA P.
ZADO, Administrative Patent Judges.
POWELL, Administrative Patent Judge.

JUDGMENT
Final Written Decision
Determining Some Challenged Claims Unpatentable
35 U.S.C. § 318(a)

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I. INTRODUCTION
MModal LLC (“Petitioner”) filed a Petition (Paper 2, “Pet.”)
requesting an inter partes review of claims 1–4, 9, 10, 12, 13, and 15–17 of
U.S. Patent No. 9,818,398 B2 (Ex. 1001, “the ’398 patent”). Nuance
Communications, Inc. (“Patent Owner”) filed a Preliminary Response.
Paper 6 (“Prelim. Resp.”). In view of those submissions, we instituted an
inter partes review of claims 1–4, 9, 10, 12, 13, and 15–17 of the ’398
patent. Paper 8. Subsequent filings include a Patent Owner Response
(Paper 16, “PO Resp.”), a Petitioner Reply (Paper 29, “Pet. Reply”), and a
Patent Owner Sur-reply (Paper 35, “Sur-reply”). An oral hearing was held
on February 27, 2019, and a copy of the transcript was entered into the
record. Paper 41.
We have jurisdiction over this proceeding under 35 U.S.C. § 6(b).
After considering the evidence and arguments of the parties, we determine
that Petitioner has proven by a preponderance of the evidence that claims 1,
3, 4, 9, 10, 12, 13, 15, and 17 of the ’398 patent are unpatentable. See 35
U.S.C. § 316(e) (2018). We also determine that Petitioner has not proven by
a preponderance of the evidence that claims 2 and 16 are unpatentable. We
issue this Final Written Decision pursuant to 35 U.S.C. § 318(a).
II. BACKGROUND
A. Related Matters
According to the parties, the ’398 patent is asserted in MModal
Services Ltd. v. Nuance Communications, Inc., Case No. 1:18-cv-00901-SCJ
(N.D. Ga. 2018). Pet. 2; Paper 5, 2.
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B. The Asserted Grounds of Unpatentability
Petitioner contends that claims 1–4, 9, 10, 12, 13, and 15–17 of the
’398 patent are unpatentable based on the following grounds:
Claims Challenged 35 U.S.C. § Reference(s)/Basis
1–4, 9, 10, 12, 13,
15–17
102(b)1 Davenport2
2, 16 103(a) Davenport, Lai3
1–4, 9, 10, 12, 13,
15–17
103(a) Baker4, Baker-6135
2, 4, 13, 16, and 17 103(a) Baker, Baker-613, Jamieson6
Petitioner relies on Declarations of Homayoon Beigi, Ph.D.
(Exs. 1003, 1047). Patent Owner relies on the Declaration of John L.
Hansen, Ph.D. (Ex. 2001).

1 The Leahy-Smith America Invents Act (“AIA”), Pub. L. No. 112-29, 125
Stat. 284, 287 (2011), amended 35 U.S.C. § 103. Because the application
from which the ’946 patent issued was filed before March 16, 2013, the
effective date of the relevant amendment, the pre-AIA version of §§ 102 and
103 applies.
2 U.S. Patent Application No. 2002/0184022 A1, pub. Dec. 5, 2002
(Ex. 1005).
3 U.S. Patent No. 6,006,183, iss. Dec. 21, 1999 (Ex. 1022).
4 U.S. Patent Application No. 2004/0186714 A1, pub. Sept. 23, 2004
(Ex. 1006).
5 U.S. Patent No. 6,122,613, iss. Sept. 19, 2000 (Ex. 1007).
6 U.S. Patent No. 7,383,172 B1, iss. June 3, 2008 (Ex. 1008).
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C. The ’398 Patent
The ’398 patent explains that automatic speech recognition (ASR)
systems can process speech to produce a recognition result. Ex. 1001, 1:17–
20. The ’398 patent discloses a method involving processing speech
recognition results that include two or more results chosen by the ASR
system as likely accurate results. Id. at 1:34–37. The method involves
“evaluating the two or more results using at least one criterion that differs
from criteria used by the ASR system in determining the two or more
result.” Id. at 1:37–40. If “the at least one criterion is met by the two or
more results,” the method involves “triggering an alert concerning one of the
two or more results.” Id. at 1:37–42. This process may alert a person
reviewing a transcript that a potential error exists in the recognition results,
which may prompt the reviewer to more carefully review the recognition
result, insuring correction of incorrect recognition results. Id. at 6:48–64.
The ’398 patent discloses a system for performing this process in
connection with Figure 1, which is reproduced below.
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Figure 1 shows speech processing system 100, which includes ASR
system 102, data storage 104, and evaluation engine 106. Id. at 9:17–25.
ASR system 102 receives speech data 104a from data storage 104 and
produces one or more recognition results. Id. at 9:17–21. ASR system 102
“can determine . . . a string of one or more words that might correspond to
the speech input.” Id. at 10:35–39. Additionally, ASR system 102
generates, “for the result, a confidence of the ASR system 102 (which may
be represented as a probability on a scale of 0 to 1, as a percentage from 0 to
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100 percent, or in any other way) that the result is a correct representation of
the speech input.” Id. at 10:39–44. ASR system 102 may produce multiple
recognition results, in which case, it may “order and filter the results in some
way so as to output N results as the results of the speech recognition
process.” Id. at 10:47–51. To order the results, ASR system 102 may rank
the results according to the confidence level that each result correctly
reflects the speech input. Id. at 10:51–55. ASR system 102 may format the
results as an “N best” list, which includes a “most likely result” or “top
result,” as well as “‘N-1’ alternative recognition results that the ASR system
has identified as the results that are next most likely, after the top result, to
be a correct representation of the speech input.” Id. at 10:55–65.
Evaluation engine 106 may process the recognition results for
indications of potential error. Id. at 9:21–25. To do so, evaluation engine
106 “may use a set of confusable words and/or phrases 106A, a set of
unlikely words 106B, a language model 106C, a semantic interpretation
engine 106D, and/or prosody and/or hesitation vocalization information
106E.” Id. at 9:30–34. Evaluation engine 106 may store any results it
produces, along with the recognition results from ASR engine 102, as
information 104B. Id. at 9:36–41. Information 104B may be used, for
example, to present a reviewer with recognition results that identify potential
significant errors identified by evaluation engine 106. Id. at 9:41–46.
The ’398 patent discusses more detail regarding a process that
evaluation engine 106 may use in connection with Figure 2, which is
reproduced below.
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Figure 2 is a flowchart showing process 200 of evaluating recognition
results. Id. at 2:10–12.
Evaluation engine 106 receives the N best results generated by ASR
system at block 202. Id. at 13:38–40. In block 204, evaluation engine 106
compares the top recognition result to the alternate recognition results. Id. at
13:41–47. This may be done “in any suitable manner.” Id. at 13:47–48. “In
some embodiments, one or more thresholds may be evaluated as part of the
review and comparison of block 204.” Id. at 13:61–62. For example,
evaluation engine 106 may determine whether the recognition results’
confidence values are above or below a threshold value to “determine
whether the confidence is sufficiently high or low (as compared to the
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threshold).” Id. at 13:63–67. The ’398 patent explains that “any suitable
fixed or variable thresholds set to any suitable value(s) may be used,” and
that “[e]mbodiments are not, for example, limited to using thresholds of 50%
or any other number that would be used to determine whether a likelihood of
something occurring indicates that thing is more likely than not to occur.”
Id. at 14:7–13. At block 206, evaluation engine 106 ascertains if the
comparison revealed indications of possibly semantically significant errors
in the recognition results. Id. at 14:18–21. In the event evaluation engine
106 identifies potential error in the recognition results, at block 208, it
triggers an alert. Id. at 14:21–23. This may happen “in any suitable way,
including by presenting a visual and/or audible message via a user interface
through which the recognition results are to be presented for review.” Id. at
14:30–33. Additionally, at block 210, evaluation engine 106 “may
optionally store information regarding the potential error that may be
semantically meaningful.” Id. at 14:34–39.
Aside from identifying errors in the recognition results produced by
ASR system 102, the ’398 patent discloses determining whether the speech
input may contain errors. Id. at 36:60–63. According to the ’398 patent,
“speech input may include a potential error when a speaker is uncertain of
the speech input that he[] or she should be providing.” Id. at 36:30–33. The
’398 patent further explains that a speaker may speak differently when
uncertain about the accuracy of what he or she is saying. Id. at 36:33–43.
Therefore, the ’398 patent explains, “an evaluation of prosody information
for speech input, which may include durational information and pitch
information, may provide an indication of whether a speaker was uncertain
of the speech input that was provided.” Id. at 36:44–49.
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The ’398 patent discusses a process of evaluating prosody information
in connection with Figure 9, which is reproduced below.

Figure 9 is a flowchart showing a process of ascertaining whether a speaker
was uncertain by evaluating prosody information. Id. at 2:44–47.
At block 902, evaluation engine 106 obtains prosody information
from ASR engine 102. Id. at 37:11–13. Evaluation engine 106 then
evaluates the prosody information at block 904 to determine the probability
that the speaker was uncertain of the provided speech input. Id. at 37:27–30.
This may involve, for example, determining whether the speaker took a long
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time to pronounce phonemes, as well as whether the speaker paused for
excessively long times. Id. at 37:63–38:43. At block 906, evaluation engine
106 “compares the likelihood of uncertainty calculated in block 904 to a
threshold likelihood to determine whether the calculated likelihood exceeds
the threshold.” Id. at 42:28–31. If so, it may be deemed that the speaker
was uncertain, and evaluation engine 106 may trigger an alert in step 908.
Id. at 42:34–40.
D. Illustrative Claim
Claims 1, 12, and 15 are independent. Each of claims 2–4, 9, 10, 13,
16 and 17 depends from one of independent claims 1, 12, and 15. Claim 1 is
illustrative of the challenged claims and recites:
1. A method comprising:
evaluating two or more results of a recognition, by an automatic
speech recognition (ASR) system on a speech input, using
at least one criterion that differs from criteria used by the
ASR system in determining the two or more results,
wherein the two or more results were identified by the
ASR system as likely to be accurate recognition results for
the speech input and comprise a first recognition result
identified by the ASR system as most likely to be a correct
recognition result for the speech input and at least one
alternative recognition result identified by the ASR system
as a potential recognition result for the speech input; and
in response to determining that the at least one criterion is met by the
two or more results, triggering presentation, via a user interface,
of an alert concerning one of the two or more results.
Ex. 1001, 51:8–24.
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III. ANALYSIS
A. Claim Construction
In an inter partes review filed before November 13, 2018, claim terms
in an unexpired patent are given their broadest reasonable construction in
light of the specification of the patent. 37 C.F.R. § 42.100(b) (2018).7
Consistent with that standard, we assign claim terms their ordinary and
customary meaning, as would be understood by one of ordinary skill in the
art at the time of the invention, in the context of the entire patent disclosure.
See In re Translogic Tech., Inc., 504 F.3d 1249, 1257 (Fed. Cir. 2007).
Only those terms that are in controversy need be construed, and only to the
extent necessary to resolve the controversy. See Nidec Motor Corp. v.
Zhongshan Broad Ocean Motor Co., 868 F.3d 1013, 1017 (Fed. Cir. 2017)
(citing Vivid Techs., Inc. v. Am. Sci. & Eng’g, Inc., 200 F.3d 795, 803 (Fed.
Cir. 1999)).
Petitioner asserts that all of the terms in the challenged claims “should
be given their ordinary and customary meaning.” Pet. 11. Petitioner
contends that “[n]o specific construction of any claim term is required
because the prior art relied on in this Petition meets each of the claim terms
under any reasonable construction.” Id. at 11–12.

7 The Office recently changed the claim construction standard used in inter
partes review proceedings. As stated in the Federal Register notice,
however, the new rule applies only to petitions filed on or after November
13, 2018, and, therefore, does not impact this matter. See Changes to the
Claim Construction Standard for Interpreting Claims in Trial Proceedings
Before the Patent Trial and Appeal Board, 83 Fed. Reg. 51,340, 51,340 (Oct.
11, 2018) (stating “[t]his rule is effective on November 13, 2018 and applies
to all IPR, PGR and CBM petitions filed on or after the effective date”).
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Patent Owner argues that, contrary to assertions in the Petition,
“evaluating two or more results of a recognition” does not encompass
evaluating just a top recognition result. PO Resp. 8–9. Patent Owner argues
that we must reject Petitioner’s assertion that this limitation “could be met
by evaluating only the top ASR result.” Id. at 9. As discussed below, for
purposes of deciding whether Petitioner has shown unpatentability of the
challenged claims, we need not address whether evaluating a top recognition
result constitutes “evaluating two or more results of a recognition.”
The parties’ disputes regarding patentability do, however, warrant
addressing other claim-construction issues. We turn now to detailed
discussions of those issues.
1. “criterion”
Petitioner asserts in its Reply that “the broadest reasonable
construction of criterion is its plain meaning, ‘a standard, rule, or test by
which something may be judged.’” Pet. Reply 7. In support of this
construction, Petitioner cites the Petition, dictionary definitions of
“criterion,” and Dr. Beigi’s testimony. Id. (citing Pet. 17–18, 33–39;
Ex. 1042, 344; Ex. 1043, 204; Ex. 1047 ¶¶ 25–28). Dr. Beigi testifies that
“[a person of ordinary skill in the art] reading the claims in the context of the
’398 patent would have understood that criterion/criteria retains” the plain
meaning noted by Petitioner. Ex. 1047 ¶ 26. Dr. Beigi cites passages of the
Specification as using the term consistent with this plain meaning. Id. ¶ 27.
Patent Owner does not dispute Petitioner’s proposed construction of
“criterion.” See generally, PO Resp.
The evidence presented by Petitioner persuades us that a person of
ordinary skill in the art would understand the broadest reasonable
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interpretation of “criterion” in view of the claims and Specification of the
’398 patent is “a standard, rule, or test by which something may be judged.”
2. “evaluating two or more results of a recognition”
Independent claim 1, for example, recites “evaluating two or more
results of a recognition, by an automatic speech recognition (ASR) system
on a speech input, using at least one criterion that differs from criteria used
by the ASR system in determining the two or more results.” Ex. 1001,
51:9–13. The Petition asserts that we should give the claim language
“evaluating two or more results of a recognition” its “ordinary and
customary meaning.” Pet. 11. The Petition contends this claim language
encompasses assessing an n-best list with its scores. Id. at 14–18. For
example, Petitioner contends that the claim language encompasses
determining “whether the top results’ scores are ‘very close’ so that an
accurate distinction between them ‘might not be possible.’” Id. at 17.
In its Response, Patent Owner disagrees, arguing that “[t]he
independent claims’ plain language requires ‘evaluating two or more results
of a recognition’ identified ‘as likely to be accurate recognition results’—
not evaluating the confidence scores used to identify those results as likely
to be accurate.” PO Resp. 13–14. Patent Owner argues that the Petition
treats confidence scores as different from recognition results. Id. at 13.
Patent Owner argues that this comports with “the challenged claims, the
’398 specification, and both experts’ testimony about how a [person of
ordinary skill in the art] would have understood ‘results of a recognition’ as
claimed.” Id.
In its Reply, Petitioner responds to that argument in maintaining that
the claim language encompasses evaluating recognized words with
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associated scores. Pet. Reply 1–6. Disagreeing with Patent Owner’s
contention that the claimed “results of a recognition” are limited to
recognized words (id. at 2), Petitioner adds that “even if one adopts [Patent
Owner’s] narrow view of ‘recognition results,’ evaluating a recognition
result is not limited to evaluating the recognized words themselves” (id. at
3). Petitioner cites the Specification as disclosing repeatedly “using any
suitable criteria” to evaluate results. Id. (citing Ex. 1001, code (57), 4:66–
5:1, 9:6–11, 11:53–56, 12:3–8, 13:25–31). Petitioner also argues that the
Specification explicitly discloses using scores to evaluate recognition results
and does not require any other evaluation, “especially in view of its repeated
exhortations that its examples are not limiting in any way.” Id. Petitioner
adds that aside from the recognized words, the Specification also discloses
other information, such as sets of confusable and unlikely words, for
evaluating the recognition results. Id. at 4.
In its Sur-reply, Patent Owner argues we should not consider the
arguments in Petitioner’s Reply, and that even if we do, those arguments
lack merit. Sur-reply 2–8. Patent Owner argues that we should disregard
the arguments from the Reply because they constitute procedurally improper
new arguments. Id. at 2–3, 5–6. Additionally, Patent Owner maintains that
the claimed “results of a recognition” do not encompass scores, as asserted
by Petitioner. Id. at 2–5. Patent Owner cites claim language and the
Specification as demonstrating that “recognition results” do not encompass
scores. Id. Patent Owner also disagrees substantively with Petitioner’s
assertion that the claim language encompasses evaluating recognized words
with associated scores. Id. at 7–8. Patent Owner argues that the portions of
the Specification cited by Petitioner either (1) do not disclose evaluating
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recognition results with associated scores, or (2) describe unclaimed subject
matter. Id.
To resolve the parties’ dispute, we need not address whether the
claimed “results of a recognition” includes scores. Rather, we can resolve
the parties’ dispute by addressing whether the claim language “evaluating
two or more results of a recognition” encompasses evaluating recognized
words with associated scores.
First, we consider Patent Owner’s argument that Petitioner’s Reply
improperly newly argued that the claim language encompasses evaluating
recognition results with associated scores. Patent Owner contends, in its
Sur-reply, that the Petition did not advance this argument, thereby depriving
Patent Owner of an adequate opportunity to present arguments and evidence
to the contrary. Sur-reply 5–8.
As noted above, the Petition asserts that we should give the claim
terms their “ordinary and customary meaning.” Pet. 11. Additionally, when
addressing the “evaluating” language of the challenged claims, the Petition
explains that evaluating an n-best list by determining “whether the top
results’ scores are ‘very close’ so that an accurate distinction between them
‘might not be possible’” constitutes evaluating “two or more ASR results
using at least one criterion that is different from the criteria used by its
ASR.” Id. at 17. We find the Petition clearly conveys Petitioner’s position
that the plain and ordinary meaning of the claim language encompasses
evaluating recognized words with associated scores.
Patent Owner’s response that “results of a recognition” do not include
scores simply fails to acknowledge the Petition’s clear assertion that the
claim language, as a whole, encompasses evaluating recognized words with
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associated scores. To the extent Patent Owner is correct in asserting that the
Petition treats scores as distinct from recognition results, this does not
diminish the Petition’s clear assertion that the claim language encompasses
evaluating recognized words with associated scores. Instead, it illustrates
that the Petition contends the claim language encompasses evaluating
recognized words with associated scores, even if the scores themselves do
not constitute part of the “results of a recognition.” Indeed, without
acknowledging expressly the Petition’s position, Patent Owner’s Response
recognizes the issue of whether the claim language encompasses evaluating
recognition results with scores, arguing that the Specification does not teach
doing so. PO Resp. 18–19 n.3. Additionally, the Sur-reply afforded Patent
Owner the opportunity to respond to this argument, and Patent Owner did
so. Sur-reply 5–8. Thus, we disagree with Patent Owner’s assertion that it
did not get an opportunity to address whether the claim language
encompasses such evaluation.
Turning to the merits of the Petition’s position on the scope of the
claim language, we start with the claim language. The claim language
explicitly states that evaluating can involve information other than the
results of the recognition. In particular, the claim language recites
“evaluating . . . using at least one criterion that differs from criteria used by
the ASR system in determining the two or more results.” Although this does
not expressly refer to scores associated with recognition results, it conveys
that the evaluating can be performed with information other than the results
of the recognition. Because the claim language conveys that the evaluation
may use information other than the results of a recognition, and because the
claim language does not exclude using the scores associated with the results
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of a recognition8, we find that the plain meaning of the claim language
encompasses evaluating results of a recognition with associated scores.
Next, we consider whether the plain meaning of the claim language is
consistent with the Specification. On this point, the parties and their
declarants view certain disclosures of the Specification differently. Noting
the Specification’s repeated disclosures of evaluating recognition results
“using any suitable criteria,” Petitioner and Dr. Beigi read the Specification
as expressly teaching evaluating recognition results by evaluating their
scores. Pet. Reply 3; Ex. 1047 ¶¶ 14–16. In support of this, Petitioner and
Dr. Beigi cite the following passages from the Specification:
In some embodiments, one or more thresholds may be evaluated
as part of the review and comparison of block 204. For example,
confidences in recognition results or likelihoods determined by
an ASR system using acoustic and/or language models may be
compared to one or more thresholds to determine whether the
confidence, likelihood, etc. is above or below the threshold.
Actions may then be taken based on the comparison to the
threshold, such as in the case that the evaluation engine
determines whether the confidence, likelihood, etc. is
sufficiently high or low (as compared to the threshold) for the
action to be taken. In some embodiments in which an evaluation
engine uses one or more thresholds as part of a review and
comparison of recognition results, any suitable fixed or variable
thresholds set to any suitable value(s) may be used, as
embodiments are not limited to using any particular values for
thresholds. Embodiments are not, for example, limited to using
thresholds of 50% or any other number that would be used to
determine whether a likelihood of something occurring indicates
that thing is more likely than not to occur. It should also be

8 Although, we recognize that the claim language “at least one criterion that
differs from criteria used by the ASR system” arguably requires the use of
information other than the scores, it does not exclude also using the scores.
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appreciated that embodiments are not limited to using thresholds,
and that some embodiments may perform the review and
comparison of block 204 without evaluating thresholds.
Ex. 1001, 13:61–14:17.
Accordingly, in some embodiments a recognition result of an
ASR system may be evaluated to determine whether the
recognition result includes a word or phrase that is unlikely to
occur in the domain of the speech input on which the recognition
result is based. When the recognition result includes an unlikely
word or phrase, any suitable action may be taken. For example,
when an indication of a potential error is detected, an alert may
be triggered to notify a reviewer that an error may be present in
the recognition result of the ASR system. When the reviewer is
notified about a potential error, the reviewer may be more likely
to closely review and, if desired, correct the error and not
inadvertently overlook the error. Determining whether a
recognition result includes an unlikely word or phrase may be
carried out in any suitable manner.
Id. at 7:63–8:10.
Patent Owner and Dr. Hansen do not read the Specification as
discussing evaluating scores to evaluate recognition results. Instead, Patent
Owner argues:
The ’398 patent describes an embodiment that uses confidence
scores output from the ASR system, but not to evaluate two or
more recognition results. ’398 patent, 15:13–61. That
embodiment uses confidence scores only to select a subset of
alternative results to evaluate, which is a preliminary step before
performing the evaluation using the different criterion.
PO Resp. 18–19 n.3. In support of this assertion, Patent Owner cites Dr.
Hansen’s testimony that
I note the ’398 patent describes an embodiment that makes use
of confidence scores output from the ASR system, but a POSA
would have understood the ’398 patent to teach that this use is
not the claimed evaluation of the two or more recognition results.
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’398 patent, 13:61-14:17, 15:13-67. The ’398 patent teaches that
this embodiment uses confidence scores only to select a subset
of alternative results to evaluate, which is a preliminary step
before performing the evaluation using the criterion that differs
from criteria used by the ASR system in determining the results.
Id. The ’398 patent does not describe this usage of confidence
scores as an evaluation of recognition results, and explicitly says
the confidence scores are used to determine “which alternative
recognition results to evaluate.” Id., 15:64-65. Moreover, a
POSA would have understood that an evaluation of confidence
scores is manifestly not an evaluation of recognition results,
which are the “string[s] of one or more words that might
correspond to the speech input” (id., 10:38-39), as discussed
above in § V.A and further below.
Ex. 2001 ¶ 58.
The Specification clearly defines the scope of its evaluation of
recognition results broadly. It explains that “[t]he evaluation of the
recognition results may be carried out using any suitable criteria.” Ex. 1001,
4:66–5:1 (emphasis added). It elaborates that
an evaluation engine (which may be part of a speech processing
system) may carry out any suitable evaluation process to
determine whether recognition results include potential
significant errors. Fig. 2 illustrates one non-limiting process that
may be used in some embodiments by an evaluation engine to
make such a determination.
Id. at 13:25–31.
As part of the process shown in Figure 2, the Specification explains
that “[i]n block 204, the evaluation engine reviews the N best results and
compares the top result to the alternative recognition results to determine
whether there are one or more discrepancies between the top result and any
of the alternative recognition result that is semantically meaningful in the
domain.” Id. at 13:41–47. The Specification also explains that this may
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involve comparing “confidences in recognition results . . . to one or more
thresholds.” Id. at 13:61–66. This portion of the Specification conveys that
comparing recognition results’ scores to thresholds constitutes an example of
a suitable process of evaluating recognition results using suitable criteria.
We do not agree with Patent Owner and Dr. Hansen’s position that the
Specification’s discussion of block 204 using scores and thresholds does not
disclose evaluating recognition results. PO Resp. 18–19 n.3.; Ex. 2001 ¶ 58.
“[T]he evaluation engine” performs block 204 to identify potential error in a
top recognition result. Ex. 1001, 13:41–47 (emphasis added). The
disclosure of “the evaluation engine” using scores and thresholds when
reviewing recognition results for potential error conveys that the system
evaluates the recognition results using the scores and thresholds. We find
that a person of ordinary skill in the art would understand the Specification
as disclosing evaluation of recognition results with their associated scores,
such as by comparing the scores to one or more thresholds. See, e.g., id. at
4:66, 7:63–8:10, 13:25–31, 13:60–14:17.
Patent Owner argues that the discussion of the execution of block 204
is an “introductory discussion . . . of the embodiment described more fully at
15:13-61, which the POR (at 18-19 n.3) already explained uses confidence
scores only in a preliminary step before performing the evaluation of the
recognition results that the ‘398 patent claims.” Sur-reply 7. Patent Owner
provides no explanation or evidence of why a person of ordinary skill in the
art would understand the discussion of block 204 as only disclosing “the
embodiment more fully described” in column 15. See id. Like Patent
Owner, Dr. Hansen appears to assume that the discussion in column 15
limits the discussion of the evaluation engine performing block 204. See Ex.
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2001 ¶ 58. Also like Patent Owner, Dr. Hansen provides no explanation or
evidence to support this assumption. See id. We do not agree with the
unsupported assumption of Patent Owner and Dr. Hansen. Moreover, even
if we agreed with Patent Owner’s argument that the Specification does not
expressly disclose using scores and thresholds to evaluate recognition
results, we find that Patent Owner does not provide persuasive reasoning or
evidence to demonstrate that the Specification disavows or excludes such
evaluation of recognition results.
For the foregoing reasons, we find that the plain meaning of the claim
language encompasses evaluating results of a recognition with scores, and
that the Specification is consistent with this meaning. Accordingly, we
conclude that the broadest reasonable interpretation of “evaluating two or
more results of a recognition, by an automatic speech recognition (ASR)
system on a speech input, using at least one criterion that differs from
criteria used by the ASR system in determining the two or more results”
encompasses evaluating the recognition results with their associated scores.
B. Alleged Anticipation by Davenport
1. Overview of Davenport
Davenport discloses “[a] system that identifies recognized words from
a voice recognition system that have the lowest possibility of being correct,
and flagging those words on a user interface, to help with proofreading.”
Ex. 1005, code (57). Davenport notes that speech engines may generate an
Alts list, which usually includes more than one recognition candidate for
each recognized phrase or word. Id. ¶ 11. A corresponding confidence
value is associated with each recognition candidate. Id. ¶ 12. The
confidence value reflects the recognizer’s degree of confidence that the
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phrase or word accurately corresponds with the speaker’s utterance. Id.
According to Davenport, “virtually all dictation engines are believed to
produce a list of the different candidates and somehow score the likelihood
that the current word is the correct candidate.” Id. ¶ 13.
Davenport’s “system uses these variables to identify situations where
it is likely that recognition errors have occurred.” Id. ¶ 14. Davenport
discusses a process for doing so in connection with Figure 2, which is
reproduced below.

Figure 2 illustrates a flowchart of a process to “identify and produce an
indication showing likely misrecognition candidates.” Id. ¶ 6.
First, at 205, the system identifies a circumstance where the
confidence level of a best recognition falls below a predetermined threshold.
Id. ¶ 14. The system may, for example, use 50 percent or 70 percent as the
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predetermined threshold. Id. The system uses these values “to form a first
list, called list A.” Id.
The system also identifies, at 210, “two alternatives which have very
close scores, e.g., close enough that accurate detection of one or the other
might not be possible.” Id. ¶ 15. Davenport explains “this may use a system
of percentile rankings. The scores lying in the top 5 percentile closest scores
are taken as unusually close confidence ratings.” Id. A second list,
identified as List B, is formed using the values obtained at 210. Id.
The words of list A and list B are identified at 215, and “[t]he user
interface is modified to show at least some of the list A and list B words.”
Id. ¶ 26. The system may highlight the words on the list within the
document, such that “the users may be advised of likely misrecognitions,
thereby making it easier to proofread such a document.” Id. ¶ 27.
2. Legal Standard
“A claim is anticipated only if each and every element as set forth in
the claim is found, either expressly or inherently described, in a single prior
art reference.” Verdegaal Bros. Inc., v. Union Oil Co., 814 F.2d 628, 631
(Fed. Cir. 1987). Whether a reference anticipates is assessed from the
perspective of an ordinarily skilled artisan. See Dayco Prods., Inc. v. Total
Containment, Inc., 329 F.3d 1358, 1368 (Fed. Cir. 2003) (“[T]he dispositive
question regarding anticipation [i]s whether one skilled in the art would
reasonably understand or infer from the [prior art reference’s] teaching that
every claim element was disclosed in that single reference.” (alterations in
original)). In that regard, in an anticipation analysis, “it is proper to take into
account not only specific teachings of the reference but also the inferences
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which one skilled in the art would reasonably be expected to draw
therefrom.” In re Preda, 401 F.2d 825, 826–27 (CCPA 1968).
3. Discussion
Petitioner explains in detail how it contends, and we find based on
Petitioner’s showing, Davenport discloses each of the limitations of claims
1–4, 9, 10, 12, 13, and 15–17. Pet. 14–25. Patent Owner argues that
Davenport does not disclose certain limitations of independent claims 1, 12,
and 15. Prelim. Resp. 22–34. We turn now to detailed discussions of the
parties’ disputes regarding different challenged claims.
a. Independent Claims 1, 12, and 15
With respect to independent claims 1, 12, and 15, the parties’
arguments raise a number of disputes regarding whether Davenport discloses
“evaluating two or more results of a recognition, by an automatic speech
recognition (ASR) system on a speech input, using at least one criterion that
differs from criteria used by the ASR system in determining the two or more
results,” as recited in each of the independent claims.
Addressing “results of a recognition, by an automatic speech
recognition (ASR) system on a speech input,” Petitioner asserts that
Davenport’s discussion of a “speech recognition engine,” “speech engine,”
“dictation engine,” or “voice recognition system/engine” discloses an ASR
system. Pet. 15–16. Petitioner contends that Davenport’s ASR system uses
a “‘language model’ and/or ‘acoustic model’” to generate an n-best list with
results and confidence scores. Id. at 16–17.
Additionally, Petitioner asserts that Davenport discloses evaluating
the recognition results of the n-best list using at least one criterion that
differs from the criteria employed by the ASR. Id. at 17. Petitioner explains
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that the ASR selects the n-best results using its own language and acoustic
models, whereas “Davenport’s post-processing uses a different criterion to
further evaluate the results, namely, it evaluates whether the top results’
scores are ‘very close’ so that an accurate distinction between them ‘might
not be possible.’” Id. Petitioner elaborates that “the post-processing criteria
is a straightforward numerical comparison,” “not an acoustic model or
language model used by Davenport’s ASR.” Id. According to Petitioner,
“Davenport explains that the criterion for ‘unusually close confidence
ratings’ can be, for example, whether the scores are within the top 5
percentile of closest scores.” Id. Results meeting this criterion go on “List
B,” formed of “all words or utterances whose top two or three recognition
candidates vary with a margin that is very narrow,” Petitioner explains. Id.
at 17–18. Petitioner also notes that Davenport discusses an example of three
recognition results with “‘very close’ confidence scores: eight (score of 85);
ate (score of 83); and bait (score of 80).” Id. at 17.
Petitioner also argues that Davenport’s discussion of comparing
recognition results’ confidence scores to a threshold discloses the claimed
evaluation using a criterion different from the criteria used to identify the
recognition results. Id. at 18. Petitioner explains that Davenport discloses
this threshold “may be a number, such as a 70% confidence level, or may be
the results with the lowest 5 percentile confidence levels.” Id.
We turn now to detailed discussions of the disputes raised by the
parties’ arguments.
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(1) Whether Davenport’s Generation of “List A”
Evaluates Two or More Results of a
Recognition
Patent Owner argues that Davenport’s process of generating list A
evaluates only the score of a top recognition result, thereby failing to
disclose the independent claims’ “evaluating two or more results of a
recognition” (emphasis added). PO Resp. 11–12. We deem this argument,
which applies only to Davenport’s generation of list A, moot because we
determine for the reasons discussed throughout this Decision that Petitioner
has shown that Davenport’s generation of list B meets the “evaluating”
limitations of the independent claims.
(2) Whether Davenport Evaluates Results of a
Recognition
Patent Owner argues that Davenport’s process of determining whether
to include recognition results on list A or list B does not evaluate recognition
results. PO Resp. 12–16. Patent Owner bases this argument on its position
that the claimed “evaluating two or more results of a recognition” requires
evaluating the words themselves, rather than evaluating the words with the
associated confidence scores. Id. As explained in detail above in
Section III.A.2, we disagree with Patent Owner’s position regarding the
scope of the claims. Consequently, we find unpersuasive Patent Owner’s
argument that Davenport evaluates scores, but not recognition results.
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(3) Whether Davenport Uses a Criterion Different
From Criteria Used by the ASR System
(a) Patent Owner’s Argument that
Davenport’s Scores Are Used by the ASR
Patent Owner argues that Davenport uses confidence scores in the
ASR to determine recognition results, as well as in determining whether to
put recognition results on list A or list B. PO Resp. 18–19. Patent Owner
argues Davenport, therefore, does not disclose “evaluating two or more
results of a recognition, by an automatic speech recognition (ASR) system
on a speech input, using at least one criterion that differs from criteria used
by the ASR system in determining the two or more results,” as recited by the
claims. Id.
Patent Owner’s argument is not commensurate in scope with the
independent claims. Although this claim language requires using at least
one criterion that was not used in the determining the two or more results, it
does not exclude also using some criteria that were used in determining the
two or more results. Therefore, even if Davenport uses the confidence
scores to determine the recognition results and then to evaluate them, that by
itself does not distinguish the claims from Davenport. Of course, to the
extent Davenport does use the confidence scores both to determine
recognition results and subsequently evaluate them, Petitioner needs to
demonstrate Davenport uses some at least one other criterion that meets the
claims. The parties’ disputes regarding whether Davenport discloses some
other criterion are discussed in the following sections.
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(b) Whether Confidence Scores Being “Very
Close” or Below a Threshold Is a
Different Criterion
As noted above, Petitioner argues that Davenport’s evaluation of
whether the ASR’s recognition results have very close scores and the
evaluation of whether the scores fall below a threshold each involve using a
criterion that differs from the criteria used by Davenport’s ASR in
determining the recognition results. Pet. 17–18. The evidence cited by the
Petition includes Dr. Beigi’s testimony that Davenport’s “post-processor . . .
uses a different criteria: (a) its own minimum confidence threshold, and (b) a
threshold for how close the top scores are.” Ex. 1003 ¶ 125.
Patent Owner argues that “[t]he ’398 specification nowhere describes
applying a threshold to a criterion used by the ASR system as somehow
being a different criterion, because it manifestly is not.” PO Resp. 20.
Asserting that Davenport’s ASR uses confidence scores, Patent Owner
criticizes that the Petition does not analyze why applying a threshold to a
criterion used by the ASR constitutes applying a different criterion. Id. at
20–22. Patent Owner argues that “[a]s Dr. Hansen explains, the criterion
Davenport evaluates is the confidence score, which is a criterion used by the
ASR system in generating the recognition results.” Id. at 20–21.
Petitioner counters that “[a] ‘criterion,’ however, is “a standard, rule,
or test by which something may be judged,’ and not the something that is
being judged, i.e., the recognized words and their scores.” Pet. Reply 8–9.
In his Supplemental Declaration, Dr. Beigi elaborates that “a criterion might
be whether the top two or three scores are within the top 5th percentile of
closest scores,” i.e., “whether the difference between the two or three top
scores is small enough that 95% of the top scores are further apart.”
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Similarly, Dr. Beigi testifies that “the test of whether the word’s score is
above 75” is a criterion.
Patent Owner responds that each recognition result’s confidence score
is a “criterion” according to Petitioner’s construction. Sur-reply 9. Patent
Owner contends that “Davenport undisputedly only evaluates the scores that
the ASR system itself used as measures in determining the recognition
results by judging their likely accuracy.” Id. at 10.
Petitioner persuades us that, contrary to Patent Owner’s arguments,
Davenport’s evaluation to compile lists A and B does not only use
confidence scores as criteria, but also uses at least one criterion different
from the confidence scores. For example, Petitioner persuades us that a
person of ordinary skill in the art would have understood that Davenport’s
process of generating list B uses a test with a threshold, such as the
exemplary 5% value, to determine whether the recognition results’ scores
are close enough to trigger inclusion of the recognition results on the list.
Pet. 17–18; Pet. Reply 6–12; Ex. 1003 ¶¶ 125–128; Ex. 1047 ¶¶ 25–28. This
test and threshold are not the recognition results’ scores; the scores are the
scores, and the test and threshold are separate and applied to the scores.
Additionally, under the broadest reasonable interpretation of “criterion” the
test and threshold constitute “at least one criterion,” as recited in the
independent claims. Thus, regardless of whether the scores constitute at
least one criterion used by Davenport to evaluate the recognition results, the
test and the threshold applied to the scores constitutes at least one different
criterion than the scores themselves. Thus, a person of ordinary skill in the
art would have understood Davenport as disclosing that the test and
threshold used in generating list B were not used to determine the
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recognition results (discussed below in Section III.B.3.a.(3)(c)), and we
therefore find Davenport discloses “evaluating two or more results of a
recognition, by an automatic speech recognition (ASR) system on a speech
input, using at least one criterion that differs from criteria used by the ASR
system in determining the two or more results,” as recited in the independent
claims.
(c) Whether Davenport’s ASR System Uses
the Alleged Criteria in Determining
Recognition Results
Citing Dr. Beigi’s testimony, the Petition asserts that Davenport’s
post-processing uses at least on criterion different from the criteria used by
its ASR to generate recognition results. Pet. 14–18. In discussing the state
of the art, Dr. Beigi’s first Declaration explained in detail how ASRs
generate recognition results using language models, acoustic models, and
statistics. Ex. 1003 ¶¶ 52–59. Dr. Beigi also explained in detail how known
post-processing allowed error correction using various techniques. Id.
¶¶ 65–69. With this background, Dr. Beigi further testified that Davenport’s
ASR uses “language and/or acoustic models,” whereas its post-processor
“uses a different criteria: (a) its own minimum confidence threshold, and (b)
a threshold for how close the top scores are.” Id. ¶ 125.
Based on this testimony, the Petition argued that Davenport discloses
using different criteria in post-processing than in generating recognition
results with the ASR. Pet. 14–18. Discussing the state of the art in post-
processing, the Petition argued that “[u]sing the same criteria as the ASR
would not have made sense.” Id. at 7.
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Dr. Beigi testifies that Davenport discloses a post-processor that uses
at least one criterion different from the criteria used by Davenport’s ASR to
generate its n-best list. Ex. 1003 ¶¶ 119–128. Dr. Beigi explains that
Davenport’s ASR generates an n-best list with “its own ‘language model’
and/or ‘acoustic model.’” Id. ¶ 123. Dr. Beigi further explains that
Davenport’s “post-processor, however, uses a different criteria: (a) its own
minimum confidence threshold, and (b) a threshold for how close the top
scores are. These criteria are not language models or acoustic models in the
ASR. They are much simpler and straightforward numerical criteria.” Id.
¶ 125.
Patent Owner deposed Dr. Beigi about his testimony that Davenport’s
post-processor uses criteria different from the criteria used by the ASR to
generate the n-best list. Ex. 2003, 92:19–102:15. For example, Patent
Owner asked Dr. Beigi if “Davenport’s ASR use the scores that it
produces?” Id. at 96:13–14. Dr. Beigi answered:
It uses the scores that it produces, but with its own logic.· So the
criteria are different.· The scores are pieces of information, so
the ASR can use the scores in any way it wants, but once it puts
out the N-best list, it’s already put out whatever it did.· So it’s
applied all its criteria, basically.
Now the N-best list is at Davenport's disposal.· Now
Davenport continues and applies further criteria, which those
further criteria weren’t applied.· Had they been applied, he
wouldn't need apply them again.· Right?· It's just very
straightforward that this is a different criterion that's being
applied.· Otherwise, there is no need for that criteria to be applied
anymore.· Davenport is coming up with the threshold or a
percentile that’s making assumptions, and those assumptions are
the criteria that it's using.
Id. at 96:15–97:11.
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Patent Owner also asked Dr. Beigi “[i]s it impossible that the ASR
uses the same threshold that Davenport’s post-processor uses?” Id. at 98:6–
8. Dr. Beigi answered that “it’s very low probability. But it’s not
impossible.” Id. at 98:10–12.
Citing Dr. Beigi’s deposition testimony in combination with other
evidence, Patent Owner’s Response argues that the Petition did not show
that the thresholds Davenport’s system uses to generate lists A and B are not
also used by Davenport’s ASR when generating recognition results. PO
Resp. 22–23. Patent Owner asserts that the Petition does not demonstrate
express anticipation because “Davenport’s ASR system is a black box.” Id.
Patent Owner argues that the Petition does not demonstrate inherent
anticipation because Dr. Beigi admitted a possibility of Davenport’s ASR
system using the same thresholds that Davenport uses to generate lists A and
B. Id. at 23. Patent Owner concludes that “the Petition wholly fails to
establish that the alleged criteria Davenport uses to evaluate recognition
results are different from the criteria used by the ASR system in determining
the results.” Id.
In its Reply, Petitioner maintains that it demonstrates Davenport’s
system uses different criteria in post-processing for generating lists A and B
than used by the ASR to generate the n-best list of recognition results. Pet.
Reply 8–12. Arguing that it need not completely rule out the possibility that
the ASR could use the same criteria as the post-processing, Petitioner asserts
that Patent Owner’s “only supporting evidence that Davenport’s ASRs might
have used the same criteria is an expert declaration that is due no weight
because it simply repeats Nuance’s legally flawed and conclusory
arguments.” Id. at 10.
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Petitioner elaborates that Dr. Beigi “explained why a [person of
ordinary skill in the art] would have understood from Davenport that the
ASRs did not apply [the same criteria as the post-processing]. If the ASR
had already applied these criteria, then Davenport ‘wouldn’t need [to] apply
them again’ in its post-processor.” Id. at 11 (citing Ex. 2003, 97) (alteration
in original). Consistent with this, Dr. Beigi testifies that “a [person of
ordinary skill in the art] would have understood that, as a practical matter,
Davenport’s ASR does not use the same criteria as its post-processor.” Ex.
1047 ¶ 29. Dr. Beigi also testifies that the ’398 patent and various other
disclosures show post-processor criteria like those used by Davenport and
reflect a recognition in the art that it would not have made sense for post-
processing to reuse criteria already used by the ASR. Id. ¶ 31.
In its Sur-reply, Patent Owner maintains that the Petition did not show
Davenport discloses using a criterion in the post-processing that was not
used to generate recognition results. Sur-reply 10–12. Patent Owner
criticizes the Reply as “attempt[ing] to shift the burden to [Patent Owner]”
(id. at 11) and relying on procedurally improper arguments and evidence that
should have been advanced in the Petition to establish a prima facie case of
unpatentability (id. at 10–12). Id. For example, Patent Owner argues that
“Dr. Beigi’s deposition testimony that Davenport ‘wouldn’t need’ to use the
same thresholds (Reply, 11) was not cited in the Petition and cannot be used
belatedly to make the Petition’s prima facie case.” Id. at 11–12.
We find Patent Owner’s arguments that the Petition fails to
sufficiently set forth evidence and arguments establishing a prima facie
showing of unpatentability to be unavailing. Sur-reply 11–12. “[I]n an
[inter partes review], the petitioner ha[s] the burden from the onset to show
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with particularity why the patent it challenges is unpatentable.” Harmonic
Inc. v. Avid Tech., Inc., 815 F.3d 1356, 1363 (Fed, Cir, 2016). This burden
never shifts to the patent owner. Dynamic Drinkware, LLC v. Nat’l
Graphics, Inc., 800 F.3d 1375, 1378 (Fed. Cir. 2015). Here, we find
Petitioner has shown from the onset with particularity why Davenport
discloses the claim limitation at issue. As we discussed above, the Petition
sets forth expressly the position that the post-processor in Davenport uses
criteria different from that used by the ASR, stating that a post-processor
“[u]sing the same criteria as the ASR would not have made sense.” Pet. 7.
Also, citing Dr. Beigi’s testimony, the Petition asserts elsewhere that
Davenport’s post-processing uses at least one criterion different from the
criteria used by its ASR to generate recognition results. Pet. 14–18;
Ex. 1003 ¶¶ 119–128. To the extent Patent Owner takes issue with Dr.
Beigi’s testimony during his cross-examination, we do not rely on this
testimony in determining that the Petition sets forth with particularity why
Davenport discloses the claim limitation at issue. However, we do consider
this testimony is assessing whether Petitioner has shown unpatentability by a
preponderance of the evidence. “There is no requirement, either in the
Board’s regulations, in the APA, or as a matter of due process, for the
institution decision to anticipate and set forth every legal or factual issue that
might arise in the course of trial,” and “[t]he purpose of the trial in an inter
partes review proceeding is to give the parties an opportunity to build a
record by introducing evidence—not simply to weight the evidence of which
the Board is already aware.” Genzyme Therapeutic Prods Ltd. P’ship v.
Biomarin Pharm. Inc., 825 F.3d 1360, 1366–67 (Fed. Cir. 2016). Dr.
Beigi’s deposition testimony was given in response to cross-examination by
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Patent Owner’s counsel, and we find it is proper for the Board to consider
this testimony. Moreover, Patent Owner had the opportunity to address this
testimony in the Sur-reply, which was filed approximately five months after
Dr. Beigi’s deposition.
Patent Owner also argues that Davenport’s ASR could possibly use
the same thresholds that its post-processing does to generate lists A and B.
PO Resp. 23; Sur-reply 11–12. Assuming arguendo that Patent Owner is
correct, at best this would show that, theoretically, it would have been
possible to construct Davenport’s ASR to use these thresholds before
reusing them in post-processing to generate lists A and B. This, however,
neither shows that a skilled artisan would have understood Davenport to
disclose using the same thresholds in post-processing and the ASR, nor
outweighs Petitioner’s evidence, discussed above, that a person of ordinary
skill in the art would have understood Davenport as disclosing that the post-
processing uses thresholds not used by the ASR when generating recognition
results.
(4) Summary for Independent Claims 1, 12, and 15
In sum, Petitioner demonstrates, by a preponderance of the evidence,
that Davenport anticipates independent claims 1, 12, and 15.
b. Claims 2 and 16
Depending from claims 1 and 15, respectively, Claims 2 and 16 recite
“wherein the evaluating the two or more results using the at least one
criterion comprises evaluating the two or more results for medically-
meaningful discrepancies between the two or more results.” Ex. 1001,
51:25–28; 53:35–38. Petitioner notes that the claims and the Specification
“do not recite any particular methodology for finding medically meaningful
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discrepancies.” Pet. 21. With this background, Petitioner asserts that a
person of ordinary skill in the art would understand that “Davenport, like
Lai, identifies meaningful discrepancies in any domain—including the
medical field—by evaluating the ASR’s scores using its own criteria.” Id. at
22.
Petitioner elaborates that Davenport teaches identifying potential error
in circumstances where the potential recognition results include the terms
“eight,” “ate,” and “bate” with relatively close scores. Id. Petitioner asserts
that “[t]hese are meaningful discrepancies in any domain, including the
medical field, as a comparison between ‘eight broken bones’ and ‘ate broken
bones’ or ‘eight stitches’ and ‘ate stitches’ readily reveals.” Id. at 23.
Citing Lai as evidence, Petitioner also indicates that Lai and
Davenport each operate “by evaluating the ASR’s scores to detect errors
such as ‘there are signs of cancer’ that should state ‘there are no signs of
cancer.’” Id. at 22. Petitioner argues that there was an assertion during the
prosecution history of the ’398 patent that such an error constitutes a
medically-meaningful discrepancy. Id.
In its Response, Patent Owner argues Petitioner does not show
Davenport would find medically-meaningful discrepancies. PO Resp. 24–
30. Patent Owner argues that Petitioner does not show Lai or Davenport
actually would identify potential confusion between “no signs of cancer”
and “signs of cancer.” Id. at 24. Patent Owner argues that Petitioner also
fails to show Davenport actually would identify potential errors in the other
hypotheticals raised, such as “eight broken bones” versus “ate broken
bones.” Id. at 25–30.
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Patent Owner also argues that even if Davenport’s system finds
discrepancies, and some of those discrepancies happen to be medically-
meaningful, Petitioner does not show that Davenport evaluates “for
medically-meaningful discrepancies.” Id. at 30–31. Patent Owner contends
that the Specification explains that identified discrepancies may or may not
be medically-meaningful. Id. at 30.
In its Reply, Petitioner indicates that Patent Owner overestimates the
required showing and underestimates Davenport’s disclosure. Pet. Reply
12–17. Petitioner contends that “the issue is whether a [person of ordinary
skill in the art] would have understood that Davenport taught the necessary
likelihood determinations.” Id. at 14. Petitioner argues that Patent Owner
admitted a person of ordinary skill in the art would have recognized that
“Davenport’s ASR’s internal models would be trained for the relevant
domain (e.g., medical) before use so that they could determine the likelihood
of recognized words in that domain.” Id. at 13. Petitioner maintains that Lai
and Davenport show that “Davenport would identify medically-meaningful
discrepancies.” Id. at 13–15. Petitioner asserts that Patent Owner relies on
an overly narrow “moving-target construction” of the claims. Id. at 15–17.
Petitioner argues the claims “require finding ‘potential errors in the
recognition results that may be semantically significant’ in the medical
field.” Id. at 15–16.
In its Sur-reply, Patent Owner maintains that Petitioner has not shown
Davenport’s system would detect discrepancies that happen to be medically-
meaningful. Sur-reply 12–15. Patent Owner explains that “Davenport only
generates alerts under particular conditions, and the Petition provides no
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evidence that any medically-meaningful discrepancies would meet
Davenport’s alert conditions.” Id. at 14.
Patent Owner also maintains that even if Davenport’s process
identifies discrepancies that happen to be medically-meaningful, Petitioner
has not shown that Davenport discloses “evaluating for medically
meaningful discrepancies.” Id. at 15–16. Patent Owner explains that “[t]he
relevant issue is whether the system evaluates for discrepancies classified as
medically-meaningful specifically, as opposed to merely identifying
discrepancies generally.” Id. at 16.
Petitioner’s explanation of how Davenport allegedly anticipates
dependent claims 2 and 16 does not account adequately for all of the words
in the claim language “evaluating the two or more results for medically-
meaningful discrepancies.” See In re Wilson, 424 F.2d 1382, 1385, (CCPA
1970) (“All words in a claim must be considered in judging the patentability
of that claim against the prior art.”). As noted above, Petitioner argues that
Davenport “identifies meaningful discrepancies in any domain—including
the medical field—by evaluating the ASR’s scores using its own criteria.”
Pet. 22. Thus, Petitioner assumes, without persuasive support, that the
claims only require finding meaningful discrepancies, indiscriminative of
domain. This assumption reads at least the word “medically” out of the
recited claim language, which recites “evaluating . . . for medically-
meaningful discrepancies.” Ex. 1001, 51:27–28, 53:37–38 (emphasis
added).
We disagree with Petitioner’s argument that identifying discrepancies
in Davenport—i.e., such as between ate, eight, and bait—discloses the
recitation “evaluating . . . two or more results for medically-meaningful
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discrepancies between the . . . results.” Pet. 21–23. First, we disagree with
Petitioner’s assertion that Davenport “identifies meaningful discrepancies in
any domain.” Id. at 22. Davenport does not describe identifying
discrepancies that are meaningful for a domain. The Specification of the
’210 patent explains that within a particular context, i.e., domain, some
misrecognition of text errors may be significant and have serious
consequences, whereas other misrecognition errors are not significant and do
not have serious consequences. Ex. 1001, 3:23–28. Moreover,
misrecognition errors that are significant in one domain may not be
significant in a different domain, according to the Specification. Id. at 4:27–
42. Accordingly, the Specification discloses, in some aspects of the
invention, providing indications of potential significant errors that “may
include discrepancies between recognition results that are meaningful for a
domain, such as medically-meaningful discrepancies.” Id. at 4:63–66. In
contrast, Davenport does not disclose evaluating results that are meaningful
for a particular domain. For example, Petitioner relies on Davenport’s
disclosure of list B recognition results “eight,” “ate,” and “bait,” but
Petitioner does not cite to, nor do we find, disclosure in Davenport of any
evaluation of whether the discrepancies between these three results are
meaningful within a particular domain, much less for a medical domain.
Indeed, the disclosure of Davenport does not appear to be concerned with
domains at all. Petitioner nonetheless posits that the difference between the
words “ate” and “eight” could be medically meaningful, Pet. 22–23, but we
find this unpersuasive because Davenport does not evaluate these results for
medically-meaningful discrepancies.
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We also find unpersuasive Petitioner’s argument that the Specification
does not constrain how the evaluation of recognition results occur. E.g.,
Pet. 21–22. Although the Specification discloses that any suitable criteria
may be used to evaluate for medically-meaningful discrepancies, Ex. 1001,
code (57), this does not mean we should read out of the claim language that
the evaluation must be for medically-meaningful discrepancies. As argued
by Patent Owner, the Specification clearly conveys that not all discrepancies
are meaningful in the medical domain. See PO Resp. 30; Sur-reply 15–16.
Moreover, the Specification conveys that the set of discrepancies that would
be meaningful differs in different domains. This is conveyed, for example,
in the following passage from the Specification:
Further, a set of words/phrases may include words/phrases that,
when confused by an ASR system, would change a meaning of a
recognition result in a way that would be semantically significant
(e.g., significant in a domain). For example, while the words
“to” and “too” may be acoustically similar and confusable by an
ASR system and an incorrect substitution of one for the other
would be erroneous, the error may not have serious consequences
in some domains if not corrected, so that these words would not
be considered significant in these domains. Conversely, as
discussed above, in the medical context if the word "malignant"
is erroneously substituted for the word “non-malignant” or vice
versa, a patient may be improperly treated, which may have
serious consequences for the patient and the medical institution.
Ex. 1001, 19:34–48 (emphasis added). In view of this, we do not agree with
Petitioner’s assumption that the claims only require indiscriminately finding
meaningful discrepancies, some of which would happen to be meaningful in
the medical domain.
Additionally, we find unavailing Petitioner’s allegation that Patent
Owner presents a “moving-target construction.” We require Petitioner to
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explain “[h]ow the challenged claim is to be construed” and “[h]ow the
construed claim is unpatentable.” 37 C.F.R. § 42.104(b)(3), (4). And
Petitioner bears the ultimate burden of persuasion. 35 U.S.C. § 316(e).
We also find unavailing Petitioner’s observations regarding Patent
Owner’s infringement contentions in the district court. Petitioner argues that
Patent Owner identifies gender and laterality as medically-meaningful
discrepancies. Pet. 22. This assertion does not help Petitioner because
Petitioner does not present persuasive evidence that Davenport evaluates for
gender or laterality discrepancies.
Additionally, we find unavailing Petitioner’s assertion that
“Davenport’s ASR’s internal models would be trained for the relevant
domain (e.g., medical) before use so that they could determine the likelihood
of recognized words in that domain.” Pet. Reply 13. Even if accurate, this
assertion addresses models that Petitioner does not identify as used in the
“evaluating” recited in claims 1, 2, 15, and 16. Petitioner asserts that
Davenport’s ASR generates the “results of a recognition” recited in claims 1
and 15. Pet. 14–17. The Petition alleges that the “evaluating” recited in
claims 1, 2, 15, and 16 occurs in “post-processing,” not in the ASR. Id. at
17–18, 21–23. Thus, even if the ASR has provisions for domain-specific
identification of meaningful discrepancies, this does not demonstrate use of
those provisions in the post-processing that the Petition alleges to do the
“evaluating” of claims 1, 2, 15, and 16.
For the foregoing reasons, Petitioner does not demonstrate by a
preponderance of the evidence that Davenport anticipates claims 2 and 16.
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c. Claims 3, 4, 9, 10, 13, 17
The Petition explains in detail why Petitioner contends, and we find
based on Petitioner’s showing, that Davenport discloses each of the
limitations recited in these claims. Pet. 21–25. Aside from the arguments,
addressed above, regarding the patentability of the independent claim 1,
Patent Owner does not present arguments specific to dependent claims 3, 9,
or 10, provide argument other than the arguments for. Our review of the full
record in this proceeding persuades us that Davenport anticipates claims 3,
9, and 10.
Patent Owner does argue claims 4, 13, and 17 separately from the
independent claims. PO Resp. 31. Patent Owner argues that “the Petition
(at 23) alleges that Davenport anticipates claims 4, 13, and 17 merely ‘for
the same reasons as claims 2 and 16,’ which . . . are fatally flawed.” Id.
We disagree with Patent Owner’s characterization of the Petition.
Although it states that claims 4, 13, and 17 “are anticipated for the same
reasons as claims 2 and 16,” it provides additional explanation. Pet. 23. It
explains Petitioner’s contention that the disclosures of Davenport discussed
in connection with claims 2 and 16 meet the specific limitations of claims 4,
13, and 17 because “Davenport evaluates the two or more results for errors
that ‘may cause’ a change in meaning, such as its ate-eight-bait example.”
Id. In other words, rather than repeating all of the Davenport disclosures
cited as teaching the limitations of claims 2 and 16, the Petition refers back
to them and explains that those disclosures meet the limitations of claims 4,
13, and 17. Our review of the evidence persuades us that although they do
not meet the limitations of claims 2 and 16, the disclosures of Davenport
cited by Petitioner do meet the broader limitations of claims 4, 13, and 17.
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In sum, Petitioner has shown, by a preponderance of the evidence, that
Davenport anticipates claims 3, 4, 9, 10, 13, 17.
C. Alleged Obviousness over Davenport and Lai
1. Overview of Lai
Lai’s disclosure relates to speech recognition systems’ user interfaces.
Ex. 1022, 1:7–8. Lai teaches that it can be difficult to detect errors when
dictating text with speech recognition technology. Id. at 2:25–32. Lai
explains, “[f]or example, the sentence ‘there are no signs of cancer’ can
become ‘there are signs of cancer’ through a deletion error. This type of
error can be easy to miss when quickly proof reading a document.”
Id. at 2:29–32.
2. Discussion
Petitioner asserts that it would have been obvious in view of Lai to
use Davenport in the medical realm, and that doing so would meet the
limitations of claims 2 and 16. Pet. 25–26. Petitioner elaborates that
[a person of ordinary skill in the art] would have been motivated
to use Davenport in the medical domain and would have
reasonably expected to successfully identify medically
meaningful discrepancies such as . . . ‘eight/ate broken bones’
and ‘eight/ate stitches’ . . . . Lai teaches that general-purpose
approaches such as Davenport’s were used in the medical
domain because such errors are easy for a human to miss but
important to correct. “For example, the sentence ‘there are no
signs of cancer’ can become ‘there are signs of cancer’ through
a deletion error. This type of error can be easy to miss when
quickly proofreading a document.” Lai 2:25-33; Beigi Decl.
¶¶ 138-141. Thus, a [person of ordinary skill in the art] would
have been motivated to use Davenport in the medical field
because medically meaningful errors in a medical transcription
can have ‘dire consequences’ for the patient. E.g., Chang (Ex.
1012) at 724-25; Beigi Decl. ¶ 140. Indeed, [Patent Owner]
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acknowledged this fact when it obtained the ’398 patent—and
gave the same cancer vs. no-cancer example as Lai. See ’398
File History at 60.
Pet. 25–26. Petitioner also asserts that Davenport and Lai are analogous art.
Id. at 26.
This challenge of claims 2 and 16 extensively overlaps with
Petitioner’s challenge of claims 2 and 16 as allegedly anticipated by
Davenport. The significant difference between the two challenges is that the
obviousness challenge relies on Lai as having allegedly provided motivation
to use Davenport in the medical domain. Compare Pet. 21–23 with Pet. 25–
26. Assuming it would have been obvious to use Davenport in the medical
domain, for substantially the reasons explained above in Section III.B.3.b,
we find that Petitioner has not addressed adequately how the prior art meets
the claims’ limitation of “evaluating the two or more results for medically-
meaningful discrepancies between the two or more results.” Consequently,
Petitioner has not demonstrated by a preponderance of the evidence that
claims 2 and 16 would have been obvious over Davenport and Lai.
D. Alleged Obviousness over Baker and Baker-613
1. Overview of Baker
Baker discloses improving on a base speech recognition system
without changing the base speech recognition system. Ex. 1006 ¶ 56. Baker
explains that its system could function as a product added onto a
commercially available recognition system. Id. Baker discusses an example
in connection with Figure 1, which is reproduced below.
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Figure 1 is a flowchart of a process according to one embodiment of Baker.
Id. ¶ 20.
The process begins at block 100, which involves obtaining an output
hypothesis produced by a base speech recognition process. Id. ¶ 57. The
output hypothesis may include a series of speech elements “such as the base
speech recognition system would send to any application program as the
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recognition system’s choice corresponding to a given interval of speech.”
Id.
At block 110, the system may obtain a set of alternative hypotheses.
Id. ¶ 58. This may involve obtaining from the base speech recognition
system choices considered to be almost as likely as the chosen sequence. Id.
Additionally, the system may receive “the evaluation score for the top
choice and any alternate choices.” Id.
At block 120, the external system may use “a second set of different
scoring models that is separate from and external to the base speech
recognition process” to score the top choice and alternative hypotheses.
Id. ¶ 59. For example, the external system may use “its own acoustic
models and language model, external to the base speech recognition system,
to rescore each hypothesis on the list of alternate choices that has
generated.” Id. The hypothesis with the best score is then chosen in block
130. Id. Baker provides further details regarding one embodiment of the
process of rescoring hypotheses in connection with Figure 2, which is
reproduced below.
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Figure 2 is a flowchart illustrating one embodiment of a process involving
rescoring hypotheses with a second set of scoring models. Id. ¶¶ 61–63.
The process illustrated in Figure 2 “is premised, at least in part, on
obtaining alternate hypotheses and scores therefor from the base speech
recognition process, where the scores are based on the scoring models used
in the base speech recognition process.” Id. ¶ 61. Block 200 involves
selection of a diminished set of alternative hypotheses that have good scores,
as ascertained by the scoring models used by the base speech-recognition
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process. Id. Two of the chosen hypotheses are compared at block 210 to
identify which speech element or elements differ between the hypotheses.
Id. ¶ 62. “[U]sing the second set of scoring models,” one or more of the
differing speech elements are rescored at block 220. Id. ¶ 63. At block 230,
the hypothesis having the best score is chosen from the rescored hypotheses.
Id. ¶ 64.
Baker discusses an alternate embodiment in connection with Figure 3,
which is reproduced below.

Figure 3 is a flowchart illustrating a different process of identifying a
hypothesis with a best score. Id. ¶¶ 65–69, Fig. 3.
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At block 300, “a confusable one or more speech elements in the
output hypothesis are detected.” Id. ¶ 65. This may involve referencing “a
database of confusable elements or elements that are often deleted in
speech.” Id.
Block 310 involves obtaining for at least one of the identified
confusable speech elements an alternative speech element. Id. ¶ 66. This
may involve obtaining the alternative speech element from the database of
confusable or often deleted speech elements. Id. Utilizing the alternative
speech element, a new hypothesis is generated at block 320. Id. ¶ 67.
Block 330 involves scoring the new hypothesis, which may be done “using
the second set of scoring models.” Id. ¶ 68. The hypothesis having the best
score is chosen at block 340. Id. ¶ 69. Baker also discloses alternate
processes of identifying best-scoring hypotheses in connection with
Figures 4 and 5. Id. ¶¶ 72–75.
Referring back to Figure 1, once “the rescoring system has accepted
or corrected the top choice speech element sequence the new, possibly
corrected sequence will be presented to the user or sent to an application
program in block 140, as if it had come directly from the base recognition
system.” Id. ¶ 76. Block 150 involves collecting “error correction data or
other feedback information” from the user. Id. ¶ 77. At block 160, the
information could be applied to improve the base speech recognition
procedure and/or the second set of scoring models. Id. ¶ 79.
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2. Overview of Baker-613
Baker-613 discloses using two different speech recognizers to process
speech input. Ex. 1007, code (57). Baker-613 illustrates a system with two
speech recognizers in Figure 3, which is reproduced below.9 Id. at 4:29–30.

Figure 3 shows a system that includes real-time recognizer 303, offline
recognizer 309, combiner 311, and offline transcription station 313. Id.
at 5:64–66, 6:13–18, 6:40–44.
Real-time recognizer 303 receives a speech detection sample from
microphone 301. Id. at 5:64–66. Real-time recognizer 303 does speech
recognition on the sample in real time and delivers recognized text to
monitor 305. Id. at 6:3–6.

9 Specifically, the version of Figure 3 reproduced below is the one appearing
in the Certificate of Correction for Baker-613. Ex. 1007, 25–26.
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The speech sample from real-time recognizer may also be transmitted
to offline recognizer 309, as well as combiner 311. Id. at 6:13–18. Offline
recognizer 309 may then perform independent recognition analysis, “for
example, using a LVSCR recognizer such as the HTK system.” Id. at 6:29–
32. Offline recognizer 309 may transmit its recognition results to
combiner 311. Id. at 6:29–35.
Having received both sets of recognition results, combiner 311
“processes the results by generating a combined set of recognition results
and by checking for instances of uncertainty by one or both of the
recognizers or discrepancies between the results produced by the two
recognizers.” Id. at 6:35–40. Combiner 311 transmits “the speech sample
and the combined set of recognition results, including information that
identifies instances of recognition uncertainty or disagreement, to the offline
transcription station 313.” Id. at 6:40–44. Using the speech sample and the
input from combiner 311, a human operator at offline transcription station
313 “generate[s] an essentially error-free transcription of the speech
sample.” Id. at 6:44–48.
3. Discussion
Petitioner identifies where it contends, and we find Petitioner has
shown, how Baker and Baker–613 teaches each limitation of claims 1–4, 9,
10, 12, 13, and 15–17. Pet. 28–55. Specifically, Petitioner argues that
Baker teaches most of the limitations of claims 1–4, 9, 10, 12, 13, and 15–
17. Id. For example, Petitioner asserts that Baker teaches the “evaluating”
step of independent claim 1. Id. at 29–33. Petitioner contends that Baker
determines two or more speech recognition results with first scoring models,
followed by using a different set of scoring models to rescore each of the
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speech-recognition results. Id. at 31. Petitioner argues that Baker “selects
and presents to the user the best of the n-best hypotheses.” Id. at 35.
Petitioner notes that Baker does not teach triggering an alert.
Id. at 33. Petitioner argues, however, that “Baker and Baker-613 together”
teach rescoring the ASR’s results with at least one criterion to trigger an
alert. Id.
Petitioner explains that Baker-613 teaches triggering an alert when it
detects uncertainty in speech recognition results. Id. at 36–37, 41.
Petitioner cites Baker-613 as teaching identification of uncertainty when an
ASR produces recognition results with close scores or when two ASRs reach
different results. Id. at 36–37. Petitioner argues that a person of ordinary
skill in the art would have applied Baker-613’s teachings to Baker to
identify instances of uncertainty to which the user should be alerted. Id. at
37. Petitioner argues that the criteria for identifying uncertainty “are
applicable whether Baker individually scores each of the n-best list or
applies its discriminative models.” Id. Petitioner also argues that “a [person
of ordinary skill in the art] would have understood that post-processing
systems such as the Baker combination typically identify recognition
uncertainty . . . if all of the candidates’ scores fail to meet a minimum
threshold.” Id. at 38.
Petitioner asserts, and we are persuaded, that a person of ordinary skill
in the art “would have been motivated to combine Baker with Baker-613 to
identify and alert the user to ensure that the user does not miss an important
potential error rather than simply providing the best-known result with no
indication of the system’s uncertainty.” Id. at 41. Petitioner alleges various
considerations that would have contributed to this motivation. Id. at 41–45.
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We turn now to detailed discussions of the disputes raised by the
parties’ arguments.
a. Whether It Would Have Been Obvious to Combine
Baker and Baker-613
Patent Owner argues that Petitioner does not advance a supportable
reason that a person of ordinary skill in the art would have applied the alerts
of Baker-613 in Baker’s system. PO Resp. 42–50. Patent Owner argues that
Baker’s speech recognition process relates to the base speech recognition
process relate to one another differently than Baker-613’s two different
speech recognizers. Id. at 44. Patent Owner argues that “Baker-613 uses
two parallel recognizers that perform the same task—a ground-up
recognition on speech input, seeking to identify the most likely recognition
candidates from an unlimited universe of possibilities.” Id. On the other
hand, Patent Owner contends that “Baker uses serial recognition stages that
do not perform the same task.” Id. Patent Owner asserts that the criteria
used by Baker-613 to identify uncertainty do not apply to Baker because
Baker’s serial recognition processes only improve the recognition results
from the base speech recognition. Id. at 45–46. With Baker’s system only
improving the results and only outputting the improved results, close results
and changes during the improvement process do not indicate any
uncertainty, Patent Owner argues. Id. at 45–48. Additionally, Patent Owner
contends that Petitioner fails to objectively support its assertion that low
scores or certain circumstances during discriminative evaluation would
indicate uncertainty. Id. at 48–50.
In its Reply, Petitioner maintains that the criteria used to signal
uncertainty in Baker-613 would also signal uncertainty in Baker. Pet.
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Reply 20–23. Petitioner disagrees with Patent Owner’s suggestion that
Baker’s process for generating more accurate results eliminates the
uncertainty present in Baker-613. Petitioner explains that just as Baker’s
post-processing produces more accurate recognition results than the base
speech recognition, Baker-613’s offline recognizer generates more accurate
results than its real-time recognizer, yet flags uncertainty in its results. Id. at
20. Petitioner argues that Patent Owner did not support its arguments that
Baker’s system would not present the same uncertainty concerns as Baker-
613’s. Id. at 19. Petitioner also maintains that the evidence supports its
assertions regarding uncertainty in instances of low scores and certain
circumstances related to discriminative modeling. Id. at 21, 23.
In its Sur-reply, Patent Owner maintains that Baker’s system differs
from Baker-613’s fundamentally. Sur-reply 18–22. Patent Owner explains
that Baker-613’s two ASRs operate in parallel, whereas Baker-613’s
processes occur serially. Id. at 18–19. Patent Owner argues that Baker’s
post-processing improves the results of the base speech recognition,
eliminating uncertainty. Id. at 19–21.
Petitioner persuades us that a person of ordinary skill in the art would
have had reason to combine Baker-613’s teachings regarding flagging
uncertainty with the system taught in Baker. As Petitioner asserts, each
reference teaches a system with two different speech-recognition
evaluations, one of which tends to produce more accurate results. Pet. Reply
20. Baker-613 teaches that such a systems may detect and flag uncertainty
when either of the speech-recognition processes (including the ostensibly
less accurate process) identifies closely scored results, or when the two
speech-recognition processes identify different results. Ex. 1007, 11:12–30;
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Fig. 13. These similarities strongly support Petitioner’s position that a
person of ordinary skill in the art would have recognized that the criteria
used by Baker-613 would lend themselves to identifying and flagging
uncertainty in the results produced by Baker.
Patent Owner’s arguments about differences between the references
do not undermine Petitioner’s position. Patent Owner’s observation that one
reference processes results in parallel and the other processes serially does
not diminish Petitioner’s observation that each reference has two separate
processes, one of which ostensibly produces more accurate results. Sur-
reply 18–19; Pet. Reply 20. Petitioner persuades us that a person of ordinary
skill in the art would glean from Baker-613 that certain aspects of both the
more-accurate and the less-accurate process indicate uncertainty. Patent
Owner does not provide persuasive evidence that this understanding would
apply only to parallel processing, as in the Baker-613 reference.
We also find unavailing Patent Owner’s observation that Baker never
outputs the results of the base recognition process to a user. PO Resp. 46–
47. We agree with Patent Owner that this aspect of Baker differs from
Baker-613, which outputs the results of both real-time recognizer 303 offline
recognizer 309, as well as combining the results for presentation to a
transcriptionist. But Baker-613 flags uncertainty in the combined results
prepared for presentation to a transcriptionist. Ex. 1007, 11:12–30. This
teaching of flagging uncertainty in the results prepared for presentation to a
transcriptionist would apply to the results that Baker outputs from its post-
processing, regardless of whether Baker outputs the results of its base
speech-recognition.
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In sum, Petitioner persuades us that it would have been obvious to
combine the teachings of Baker-613 with those of Baker in the manner
proposed by Petitioner.
b. Whether the Combination Meets the Limitations of
the Claims
(1) Independent Claims 1, 12, and 15
(a) Whether the Recognition Results of
Baker’s Base Speech Recognition
Constitute “Results of a Recognition, by
an Automatic Speech Recognition (ASR)
System on Speech Input”
The Petition asserts that Baker’s base speech recognition process
outputs “two or more results of a recognition, by an automatic speech
recognition (ASR) system on a speech input,” as recited in claims 1, 12, and
15. Pet. 30–33. Patent Owner disagrees. PO Resp. 52–56.
Patent Owner argues that the Specification clearly conveys
that the ASR system “process[es] input speech to yield a
recognition result,” including a “top recognition result”
“present[ed] . . . via a display” or in the “text of a document,”
and can be composed of “one or more systems that apply any
suitable ASR technique(s) to speech input to perform a speech
recognition on the speech input.”
Id. at 54 (alterations in original). In view of this, Patent Owner argues that
the results of Baker’s base speech recognition process cannot correspond to
the claimed “results of a recognition, by an automatic speech recognition
(ASR) system” because “Baker’s system does not output any hypothesis of
the base recognition as the recognized text, and instead outputs to the user
only the results of the rescoring as the text recognized by the ASR system.”
Id. at 55.
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In its Reply, Petitioner maintains that the results of Baker’s base-
speech recognition process constitute “results of a recognition,” as recited in
the independent claims. Pet. Reply 23–25. Petitioner notes that Patent
Owner “admits ‘Baker uses a commercially available ASR system as its base
recognizer.’” Id. at 24. Petitioner argues that the Specification discusses
optionally presenting an ASR’s output to the user, but does not require doing
so. Id. Indeed, Petitioner argues, the ’398 patent conveys that an ASR
system need not display text to a user. Id. Petitioner explains that “[l]ike
Baker, the patent displays text to the user after post-processing.” Id.
Patent Owner responds that the ’398 patent teaches displaying the top
recognition result from the ASR system. Sur-reply 24. In contrast, Patent
Owner argues, Baker’s base process and rescoring cooperate to generate the
recognized text, making them internal components of a single ASR system.
Id.
We find Petitioner’s arguments and evidence persuasive. Dr. Beigi
testifies that “Baker’s ‘base recognition process’ (sometimes called ‘first
speech recognition’) corresponds to the claimed ASR. Ex. 1003 ¶ 167. The
’398 patent uses the term ASR as it is commonly understood: it is common
automatic speech recognition systems that ‘process input speech to yield a
recognition result corresponding to the speech.’” Id. (quoting Ex. 1001,
1:16–19). Dr. Beigi notes that the ’398 patent explains that “[s]ome ASR
systems may produce as output from a speech recognition process results
formatted as an ‘N best’ list of recognition (N being two or more) that
includes a top recognition result and N–1 alternative recognition results.”
Ex. 1001, 8:27–33. Dr. Beigi testifies that Baker’s base speech recognition
process functions in this manner. Ex. 1003 ¶ 167. We find this and
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Petitioner’s other evidence firmly supports the assertion that the results of
Baker’s base speech recognition process constitute “results of a recognition,
by an automatic speech recognition (ASR) system.” Pet. 29–33; Pet.
Reply 23–25.
We find Patent Owner’s arguments and evidence unpersuasive.
Patent Owner does not reconcile persuasively its admission that “Baker uses
a commercially available ASR system as its base recognizer” with its other
arguments. PO Resp. 54. Patent Owner contends that Baker’s base speech
recognizer would be an ASR system according to the ’398 patent if and only
if its top recognition result were displayed to a user. Id. But Patent Owner
does not cite persuasive evidence that the ’398 patent requires that the top
recognition result of an ASR system be displayed without further processing.
We agree with Petitioner that the portions of the Specification cited by
Patent Owner do not compel a conclusion that the recognition results of an
ASR system must be displayed without further processing. Pet. Reply 24.
For the foregoing reasons, Petitioner persuades us that the results of
Baker’s base speech recognition process constitute “results of a recognition,
by an automatic speech recognition (ASR) system on a speech input,” as
recited in independent claims 1, 12, and 15.
(b) “Evaluating Two or More Results of a
Recognition, . . . , Using At Least One
Criterion That Differs from Criteria
Used by the ASR System in Determining
the Two or More Results . . . .”
Each of independent claims 1, 12, and 15 recites
evaluating two or more results of a recognition, by an
automatic speech recognition (ASR) system on a speech input,
using at least one criterion that differs from criteria used by the
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ASR system in determining the two or more results, wherein the
two or more results were identified by the ASR system as likely
to be accurate recognition results for the speech input and
comprise a first recognition result identified by the ASR system
as most likely to be a correct recognition result for the speech
input and at least one alternative recognition result identified by
the ASR system as a potential recognition result; and
in response to determining that the at least one criterion is
met by the two or more results, triggering presentation, via a user
interface, of an alert concerning one of the two or more results.
Ex. 1001, 51:9–24, 52:38–53, 53:18–34.
Petitioner contends that, in combination, Baker and Baker-613 meet
these limitations of the independent claims. Pet. 28–45. Petitioner concedes
“[w]hile Baker uses different models to re-score the ASR’s results, it does
not teach doing so using at least one criterion that will also be used to trigger
an alert . . . . However, Baker and Baker-613 together do.” Id. at 33.
Petitioner cites Baker-613 as teaching identification of uncertainty when an
ASR produces recognition results with close scores or when two ASRs reach
different results. Id. at 36–37. Petitioner argues that a person of ordinary
skill in the art would have applied Baker-613’s teachings to Baker to
identify instances of uncertainty to which the user should be alerted. Id. at
37. Petitioner argues that the criteria for identifying uncertainty “are
applicable whether Baker individually scores each of the n-best list or
applies its discriminative models.” Id. Petitioner also argues that “a [person
of ordinary skill in the art] would have understood that post-processing
systems such as the Baker combination typically identify recognition
uncertainty . . . if all of the candidates’ scores fail to meet a minimum
threshold.” Id. at 38.
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In view of Baker-613, Petitioner argues that it would have been
obvious to combine Baker and Baker-613 by
applying Baker’s rescoring processes (that are explicitly
different than those used by its ASR) and determining if (i) two
or more top scores from the ASR or post-processor are very
close, (ii) the ASR and the post-processor rescoring models did
not all agree on one top result, and (iii) all of the scores and/or
rescores fall below an minimum acceptable value.
Id. at 39.
Patent Owner argues that, regardless of which of the identified
uncertainty criteria is used, the combination of Baker and Baker-613 does
not meet the limitations of independent claims 1, 12, and 15. PO Resp. 56–
61. Patent Owner argues that the proposed Baker combination evaluates the
scores of recognition results, not the recognition results. Id.
Patent Owner also argues that Petitioner does not demonstrate that the
Baker combination meets the limitation of “evaluating two or more results of
a recognition, by an automatic speech recognition (ASR) system on a speech
input, using at least one criterion that differs from criteria used by the ASR
system in determining the two or more results.” Id. at 57–61. Patent Owner
first argues that Petitioner does not demonstrate the scores used to identify
uncertainty are not used by the ASR to identify recognition results. Id. at
57–58. Patent Owner also argues that
[t]he claims require more than evaluating any two speech
recognition hypotheses; they require evaluating results of a
recognition by the ASR system, including a recognition result
identified by the ASR system as most likely to be correct and an
alternative recognition result identified by the ASR system. The
Petition fails to establish that any of the five alert conditions meet
these claim requirements.
Id. at 59.
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Weighing the parties’ arguments and evidence, we find that the
proposed combination of Baker and Baker-613 would meet the limitations of
independent claims 1, 12, and 15. We first address the dispute raised by
Patent Owner’s argument that the Baker combination evaluates the scores
associated with recognition results, rather than evaluating the recognition
results themselves. Id. at 56–57. As explained above in Section III.A.2, we
conclude that the claims encompass evaluating recognition results by
evaluating their associated scores. Accordingly, Patent Owner’s argument
that the Baker combination evaluates recognition results scores, instead of
evaluating the recognition results themselves, does not undermine
Petitioner’s persuasive evidence that the Baker combination teaches
“evaluating two or more results of a recognition.”
Next, we turn to the dispute raised by Patent Owner’s argument that
Petitioner does not demonstrate the scores used in the evaluation were not
also used in identifying the recognition results. Id. at 59. This argument is
not commensurate in scope with the independent claims, which recite
“evaluating . . . using at least one criterion that differs from criteria used by
the ASR system in determining the two or more results.” E.g. Ex. 1001,
51:9–13. Although this claim language requires using at least one criterion
that was not used in the determining the two or more results, it does not
exclude also using some criteria that were used in determining the two or
more results. Petitioner persuades us that the proposed combination of
Baker and Baker-613 uses at least one criterion different from those used in
determining the recognition results. For example, the Petition conveys that
the combination would identify uncertainty by using not only the values of
the scores, but also some separate criterion, such as a threshold value, for
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identifying whether the scores are “close together,” which indicates
uncertainty. See, e.g., Pet. 39.
Next, we consider the dispute raised by Patent Owner’s argument that
none of the five alert conditions meets the requirements of the claims.
Patent Owner argues that the first alert condition of close scores from the
base recognition process does not meet the claim limitations because “the
base recognition’s hypotheses are not recognition results of the Baker
Combination’s ASR system. Thus, they also are not identified by the ASR
system as most likely to be correct and an alternative recognition result as
claimed.” PO Resp. 59. This argument builds on Patent Owner’s argument
that Baker’s base speech recognition process does not constitute an ASR
system that generates recognition results. For the reasons explained above
in Section III.D.3.b.(1).(a), we find this argument unpersuasive.
In sum, weighing the parties’ arguments, we find that the proposed
combination of Baker and Baker-613 meets each of the limitations of
independent claims 1, 12, and 15. In particular, we find persuasive at least
Petitioner’s assertion that modifying Baker to identify uncertainty if its base
speech recognition scores are close results in a system that meets each of the
limitations of the challenged independent claims.
(c) Summary for Independent Claims 1, 12,
15
In sum, Petitioner persuades us that the Baker combination teaches all
of the limitations of independent claims 1, 12, and 15, and provides
persuasive rationale to combine the references (Section III.D.3.a). For the
reasons stated above, Petitioner demonstrates, by a preponderance of the
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evidence, that claims 1, 13, and 15 would have been obvious over Baker and
Baker-613.
(2) Claims 2 and 16
As discussed in Section III.B.3.b above, the Petition asserts that the
’398 patent does not specify any particular approach for identifying
medically-meaningful discrepancies. Pet. 48. Similar to the Petition’s
arguments regarding the alleged anticipation of claims 2 and 16 by
Davenport (discussed above in Section III.B.3.b), the Petition argues that
“the Baker combination identifies meaningful discrepancies in any domain,
including the medical field.” Id. at 49. The Petition elaborates that a person
of ordinary skill in the art would understand that certain medically-
meaningful discrepancies “could be detected by identifying when the ASR
or post-processor results indicate uncertainty.” Id. The Petition argues that
it would have been obvious to use the Baker combination in the medical
field. Id. at 50. Given this, Petitioner contends that the Baker combination
would have “evaluated its ASR’s two or more results for, and identified,
medically meaningful discrepancies.” Id.
The Petition adds that “even if the claims are narrower—requiring a
model that specifically evaluates the two or more results using criterion
rooted in the medical domain, i.e., evaluating medical terminology in
particular—the claims are still obvious.” Id. The Petition elaborates that
Baker’s rescoring models have statistical language models that determine a
result’s probability by referencing a language example from a relevant
domain like the medical field. Id. at 51. According to the Petition, “[t]hus,
the Baker combination would be used in the medical domain . . . , and it
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already evaluates two or more results for medically meaningful
discrepancies using criteria rooted in the medical domain.” Id.
In its Response, Patent Owner contends Petitioner does not
demonstrate that the Baker combination would have been used in the
medical domain. PO Resp. 61–63. Noting that Petitioner cites certain
potential medical-field errors as the motivation for using the Baker
combination in the medical field, Patent Owner argues Petitioner does not
demonstrate that the Baker combination would identify those errors. Id.
Patent Owner also argues that Petitioner does not show that the Baker
combination finds medically-meaningful discrepancies between recognition
results. Id. at 63–65. Patent Owner argues that Petitioner relies on
hypothetical examples of alternative recognition results with medically-
meaningful discrepancies. Id. at 63–64. Patent Owner argues that Petitioner
does not demonstrate that the hypotheticals have medically-meaningful
discrepancies. Id. at 64. Patent Owner also asserts that Petitioner does not
demonstrate that the Baker combination would identify the hypothetical
results as having medically-meaningful discrepancies. Id. at 64–65.
Patent Owner also argues that even if the Baker combination finds
discrepancies, and some of those discrepancies happen to be medically-
meaningful, Petitioner does not show that Davenport evaluates “for
medically-meaningful discrepancies.” Id. at 65. Patent Owner contends that
the Specification explains that identified discrepancies may or may not be
medically-meaningful. Id.
In its Reply, Petitioner contends that it “established that the Baker
combination taught evaluating for meaningful discrepancies in any domain,
including medical, especially because its language models take into account
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the speech’s context, determining whether they are likely to occur in the
domain.” Pet. Reply 26–27. Petitioner argues that Patent Owner concedes
“Baker’s language models would have been trained on a relevant corpus
before use in a specialized domain (e.g., medical) so that they can determine
the likelihood of the recognized words in the specialized context.” Id. at 27.
Petitioner adds that “the expectation of success need only be reasonable, not
absolute.” Id. at 28.
In its Sur-reply, Patent Owner maintains that Petitioner does not
demonstrate the Baker combination would identify any medically-
meaningful discrepancies. Sur-reply 26. According to Patent Owner,
having models “trained on a relevant corpus” does not show that the Baker
combination would detect medically-meaningful discrepancies. Id.
Like the challenge of claims 2 and 16 as allegedly anticipated by
Davenport, the challenge of claims 2 and 16 as allegedly obvious over the
Baker combination does not account adequately for all of the words in the
claim language “evaluating the two or more results for medically-
meaningful discrepancies.” For the same substantive reasons as discussed
above in Section III.B.3.b, Petitioner’s assertion that the Baker combination
meets claims 2 and 16 because “the Baker combination identifies
meaningful discrepancies in any domain, including the medical field” reads
at least one of the words “for” and “medically” out of the claims. Therefore,
this assertion, as well as the associated supporting arguments and evidence,
fail to carry Petitioner’s burden of showing unpatentability of claims 2 and
16.
We also find unavailing Petitioner’s argument regarding the statistical
language models used by Baker’s rescoring models. Claims 2 and 16
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require “evaluating the two or more results for medically-meaningful
discrepancies between the two or more results.” Ex. 1001, 51:27–28, 53:37–
38 (emphasis added). According to Petitioner and Dr. Beigi, with the
statistical language models, “a result’s probability is determined by
comparing it to a language sample from the domain, such the medical field
or a particular specialty.” Pet. 51; Ex. 1003 ¶ 205. Neither Petitioner nor
Dr. Beigi explains persuasively how determining a result’s probability, as
Baker allegedly does with its statistical language models, constitutes
evaluating for medically-meaningful discrepancies between two or more
results. To the extent Baker’s statistical language models help adapt Baker
to the medical domain in some general sense, such as by improving
estimation of a recognized word’s probability in the medical domain, that
does not explain how the Baker combination meets the specific requirements
of claims 2 and 16.
For the foregoing reasons, Petitioner fails to demonstrate obviousness
of claims 2 and 16 over Baker and Baker-613 by a preponderance of the
evidence.
(3) Claims 3, 4, 9, 10, 13, 17
The Petition explains in detail why Petitioner contends, and we find,
the Baker combination teaches all of the limitations of these claims.
Pet. 45–55. Patent Owner does not, for dependent claims 3, 9, or 10,
provide argument other than the arguments for independent claim 1. Our
review of the full record in this proceeding persuades us that the Baker
combination teaches all of the limitations of claims 3, 9, and 10.
Patent Owner does, for claims 4, 13, and 17, provide arguments in
addition to those for the independent claims. PO Resp. 65. Patent Owner
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argues that “the Petition (at 55) alleges that claims 4, 13, and 17 ‘are obvious
for the same reasons as claims 2 and 16,’ which . . . are fatally flawed.” Id.
We disagree with Patent Owner’s characterization of the Petition.
Although the Petition states that claims 4, 13, and 17 “are obvious for the
same reasons as claims 2 and 16,” it provides additional explanation.
Pet. 54–55. It explains Petitioner’s contention that the disclosures of Baker
combination discussed in connection with claims 2 and 16 meet the specific
limitations of claims 4, 13, and 17 because “the Baker combination
determines whether the two or more results indicate an a potential error by
detecting uncertainty in the scores or rescore” and “the potential errors
identified by the Baker combination ‘may cause’ the meaning to differ from
the speech input, as recited in these claims.” Id. at 55. In other words,
rather than repeating all of the Davenport disclosures cited as teaching the
limitations of claims 2 and 16, the Petition refers back to them and explains
that those disclosures meet the limitations of claims 4, 13, and 17. Our
review of the evidence persuades us that although Petitioner does not show
that it meets the limitations of claims 2 and 16, Petitioner does demonstrate
that the Baker combination meets the broader limitations of claims 4, 10,
and 17.
In sum, Petitioner persuades us that the Baker combination teaches all
of the limitations of claims 3, 4, 9, 10, 13, 17, and provides persuasive
rationale to combine the references (Section III.D.3.a). For the reasons
stated above, Petitioner demonstrates, by a preponderance of the evidence,
that claims 3, 4, 9, 10, 13, 17 would have been obvious over Baker and
Baker-613.
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E. Alleged Obviousness over Baker, Baker-613, and Jamieson
1. Overview of Jamieson
Jamieson discloses a system and method for processing speech.
Ex. 1008, 1:20–21. Jamieson explains that “[u]sers dictating text with
speech recognition find that errors are hard to detect.” Id. at 3:1–2.
Jamieson elaborates that doctors may miss subtle mistakes that change the
meaning of a report, possibly affecting clinical care. Id. at 3:19–25.
Jamieson teaches that “[s]emantic understanding of hypotheses
returned by a speech engine could improve the quality of recognition and in
cases of misrecognition speed the identification of errors and potential
substitutions.” Id. at code (57). Jamieson discloses a method that “achieves
semantic understanding by coupling a speech recognition engine to a
semantic recognizer, which draws from a database of domain sentences
derived from a document corpus, and a knowledge base created for these
domain sentences.” Id.
2. Discussion
In support of its assertion that claims 2 and 16 would have been
obvious over Baker, Baker-613, and Jamieson, Petitioner argues that “it
would have been obvious to modify the Baker combination to add
Jamieson’s semantic analysis—that is, to directly evaluate the candidate
results’ meaning—to help identify medically significant discrepancies.”
Pet. 51. Petitioner explains that Jamieson teaches its semantic analysis helps
avoid medical error. Id. at 52. Petitioner asserts that such error “could have
‘dire consequences.’” Id. Petitioner asserts that a person of ordinary skill in
the art would have been motivated to add Jamieson’s semantic analysis
capability to the combination of Baker and Baker-613 “to help identify
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uncertainty and thus improve the quality of the transcriptions and avoid any
dire consequences.” Id. at 53. Petitioner also asserts that Jamieson is
analogous art. Id. at 54.
In support of the contention that claims 4, 13, and 17 would have been
obvious over Baker, Baker-613, and Jamieson, Petitioner asserts that a
person of ordinary skill in the art “would have added Jamieson’s semantic
analysis to Baker’s uncertainty determination as explained with respect to
claims 2 and 16. As a result, the new combination would further evaluate
whether the meanings of the top results are different, thus indicating a
potential difference from the meaning of the speech input.” Id. at 55. We
turn now to detailed discussions of the disputes raised by the parties’
disagreements regarding Petitioner’s challenge of claims 2, 4, 13, 16, and 17
as allegedly obvious over Baker, Baker-613, and Jamieson.
a. Claims 2 and 16
Patent Owner argues that Jamieson does not use its semantic analysis
to identify discrepancies between recognition results. PO Resp. 67–70.
Instead, Patent Owner asserts, Jamieson applies its semantic analysis to only
one displayed result. Id. at 67. Patent Owner argues that the semantic
analysis serves only to illustrate for the user the displayed result’s meaning.
Id. at 68. According to Patent Owner, “[o]nce the displayed hypothesis’s
semantic meaning is indicated, it is up to Jamieson’s user to ‘spot’ whether
that meaning differs from what the user spoke. . . . Nowhere does Jamieson
teach comparing the semantic meaning of a top recognition hypothesis to
that of any alternative hypothesis.” Id. at 70. Consequently, Patent Owner
argues, Jamieson’s teachings do not support Petitioner’s argument that
adding Jamieson’s semantic analysis to the Baker combination would
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“identify . . . when the ASR’s top choice and highest-ranked alternatives
have opposite meanings.” Id. (quoting Pet. 54).
Petitioner counters that Patent Owner does not address the
combination of the prior art proposed in the Petition, but attacks the
references individually. Pet. Reply 28. Petitioner asserts that “the
combination uses Jamieson to evaluate for medically-meaningful differences
between the top-ranked results.” Id. at 28–29.
Patent Owner responds that Petitioner’s “alleged combination merely
‘add[s] Jamieson’s semantic analysis to the Baker combination,’ and alleges
this would result in ‘identify[ing] when the top choice and highest-ranked
alternatives have different meanings.’” Sur-reply 27 (citing Pet. Reply 28;
Pet. 51, 53–54) (alteration in original). Simply combining the references in
this manner, Patent Owner argues, would not produce the result alleged by
Petitioner. Id. Asserting that only the ’398 patent teaches a semantic
comparison of results, Patent Owner argues that Petitioner’s obviousness
contentions rest “entirely on impermissible hindsight.” Id.
Patent Owner persuades us that Petitioner does not demonstrate
obviousness of claims 2 and 16 over Baker, Baker-613, and Jamieson.
Petitioner persuades us that the ’398 patent and Jamieson recognize and
address a problem common to both. The ’398 patent expresses concern that
“if the word ‘malignant’ is erroneously substituted for the word ‘non-
malignant’ or vice versa, a patient may be improperly treated.” Ex. 1001,
19:44–47. Likewise, Jamieson recognizes that “the sentence ‘there is no
evidence of atelectasis’ can become ‘there is evidence of atelactasis’ through
a deletion error. This type of error changes the meaning of the report and
could affect clinical care.” Ex. 1008, 3:19–24.
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Patent Owner persuades us, however, that the challenged claims of the
’398 patent and Jamieson address this problem in different ways. Claims 2
and 16 of the ’398 patent address the problem by “evaluating the two or
more results for medically-meaningful discrepancies between the two or
more results.” Ex. 1001, 51:27–28, 53:37–38. Jamieson, on the other hand,
addresses the misrecognition problem by using semantic analysis to evaluate
the top recognition result and display certain information regarding the top
recognition result. Ex. 1008, 3:45–56, 4:20–24, 4:46–58, 6:60–7:9, 7:33–54,
7:65–8:4, 8:55–58. For example, “if no valid sentence hypothesis is
determined an indicator, such as a red color, is associated with the words
from the top ranked hypothesis, and is displayed in the user interface.” Id. at
4:49–54. In such an instance, “[t]he user can ask for corrections.” Id. at 8:4.
Similarly, Jamieson’s system displays a red dot beside recognition results
whose semantic meaning is abnormal and a green dot beside recognition
results whose semantic meaning is normal. Id. at 6:60–7:3. Jamieson
identifies this as an advantage, stating that “[t]he semantic type of a sentence
can be quickly displayed improving the confidence that the dictated sentence
was transcribed correctly and making it easier for the user to spot errors in a
given knowledge domain.” Id. at 8:55–58. Because Jamieson does not
teach using its semantic analysis to evaluate for medically-meaningful
discrepancies between two or more recognition results, we agree with Patent
Owner that simply adding Jamieson’s teachings regarding semantic analysis
to the Baker combination would not meet the limitations of claims 2 and 16.
As noted above, in response to Patent Owner’s argument that
Jamieson does not teach using semantic analysis in the manner required by
claims 2 and 16, Petitioner criticizes Patent Owner as attacking the
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references individually. Pet. Reply 28. Explaining that “Baker already
teaches evaluating the ASR’s results in other ways,” Petitioner argues that
“the combination uses Jamieson to evaluate medically-meaningful
differences between the top-ranked results.” Id. at 28–29.
Notwithstanding Petitioner’s argument that, generally, it is unavailing
to attack individually the references used in a combination, In re Merck &
Co., Inc., 800 F.2d 1091, 1097 (Fed. Cir. 1986) (citing In re Keller, 642 F.2d
413, 425 (CCPA 1981)), and, that bodily incorporation is not the test for
obviousness, Keller, 642 F.2d at 425, Petitioner has not explained how the
proposed combination teaches the disputed claim limitation.
Petitioner does not explain persuasively how the combination of the
references teach what Jamieson does not—evaluating for medically-
meaningful discrepancies between two or more results. Although we agree
that Baker teaches different ways of evaluating recognition results, as
explained above in Section III.D.3.b.(2), Petitioner does not persuade us that
any of those ways involves evaluating for medically-meaningful
discrepancies between two or more results. Nor does Petitioner provide
persuasive evidence that the combination of Jamieson’s semantic analysis of
the top result with Baker’s “other ways” of analyzing demonstrates
obviousness of evaluating for medically-meaningful discrepancies between
two or more results. The Petition indicates that a person of ordinary skill in
the art would have found it obvious in view of Jamieson’s teachings to
“[a]dd[] semantic analysis, . . . in addition to relying on low scores, close
scores from alternate interpretations, and/or different models disagreeing on
the results.” Pet. 53–54. This argument that it would have been obvious to
use each of the evaluating approaches taught by the Baker combination and
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Jamieson’s semantic analysis in one system fails to persuade us, as none of
the evaluating approaches meets the claims.
And Petitioner does not allege clearly, much less demonstrate
persuasively, that it would have been obvious to modify any of the different
evaluating approaches taught by the references to meet the claims.
Petitioner emphasizes that “Jamieson touts that it can quickly arrive at the
semantic meaning of a sentence, and quickly identify out-of-domain
recognitions.” Pet. Reply 29. But Petitioner does not provide persuasive
reasoning or evidence that this alleged ability would have made it obvious to
modify Jamieson’s teaching from analyzing the top recognition result to
analyzing for discrepancies between two or more results. Nor does
Petitioner allege clearly or persuasively demonstrate that Jamieson’s
teaching of semantically analyzing the top recognition result would have
made it obvious to modify one of the Baker combinations’ evaluating
approaches to meet the claims.
For the foregoing reasons, Petitioner does not show, by a
preponderance of the evidence, that claims 2 and 16 would have been
obvious over Baker, Baker-613, and Jamieson.
b. Claims 4, 13, and 17
As discussed in Section III.D.3.b.(3) above, Petitioner has shown
obviousness of claims 4, 13, and 17 over Baker and Baker-613. Petitioner
relies on Jamieson, for example, as showing the state of the art and as
support for the proposition that “a [person of ordinary skill in the art] would
have understood that post-processing systems such as the Baker combination
typically identify recognition uncertainty . . . if all of the candidates’ scores
fail to meet a minimum threshold.” E.g., Pet. 38, 43–44. Our review of the
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full record persuades us that Petitioner has shown obviousness of claims 4,
13, and 17 over Baker, Baker-613, and Jamieson.
IV. CONCLUSION
In summary,
Claims 35 U.S.C. § Reference(s)/Basis
Claims
Shown
Unpatentable
Claims Not
Shown
Unpatentable
1–4, 9,
10, 12,
13, 15–
17
102 Davenport 1, 3, 4, 9, 10,
12, 13, 15, 17
2, 16
2, 16 103(a) Davenport, Lai 2, 16
1–4, 9,
10, 12,
13, 15–
17
103(a) Baker, Baker-613 1, 3, 4, 9, 10,
12, 13, 15, 17
2, 16
2, 4, 13,
16, 17
103(a) Baker, Baker-613,
Jamieson
4, 13, 17 2, 16
Overall
Outcome
1, 3, 4, 9, 10,
12, 13, 15, 17
2, 16

V. ORDERS
In consideration of the foregoing, it is hereby
ORDERED that Petitioner has shown by a preponderance of the
evidence that claims 1, 3, 4, 9, 10, 12, 13, 15, and 17 are unpatentable;
FURTHER ORDERED that Petitioner has not shown by a
preponderance of the evidence that claims 2 and 16 are unpatentable; and
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FURTHER ORDERED that because this is a Final Written Decision,
any party to the proceeding seeking judicial review of the decision must
comply with the notice and service requirements of 37 C.F.R. § 90.2.

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PETITIONER:
Jon Strang
Inge Osman
David K. Callahan
Kevin C. Wheeler
jonathan.strang@lw.com
inge.osman@lw.com
david.callahan@lw.com
kevin.wheeler@lw.com

PATENT OWNER:

Richard Giunta
Andrew Tibbetts
Elisabeth Hunt
Daniel Wehner
rgiunta-ptab@wolfgreenfield.com
atibbetts-ptab@wolfgreenfield.com
ehunt-ptab@wolfgreenfield.com
dwehner-ptab@wolfgreenfield.com