Ex Parte Ma

Patent Trial and Appeal Board

Feb 4, 2013

11277793 (P.T.A.B. Feb. 4, 2013)

UNITED STATES PATENT AND TRADEMARK OFFICE
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BEFORE THE PATENT TRIAL AND APPEAL BOARD
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Ex parte CHANGXUE C. MA
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Appeal 2010-009737
Application 11/277,793
Technology Center 2600
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Before JOHN A. JEFFERY, MARC S. HOFF, and DANIEL N. FISHMAN,
Administrative Patent Judges.

FISHMAN, Administrative Patent Judge.

DECISION ON APPEAL
Appellant appeals under 35 U.S.C. § 134(a) from the Examiner’s
rejection of claim 20. Br. 7.1 We have jurisdiction under 35 U.S.C.
§ 6(b)(1). We affirm.

1 Throughout this opinion, we refer to: (1) the Revised Appeal Brief (“Br.”)
filed February 23, 2010; and (2) the Examiner’s Answer (“Ans.”) mailed
March 31, 2010.
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STATEMENT OF THE CASE
Appellant’s invention relates to a method for producing phonetic tag
variants in voice-to-phoneme conversion (such as is useful in voice
recognition systems). The invention generates a feature vector from a first
spoken utterance, and generates a first phonetic voice tag from that feature
vector. The invention then applies perturbations to the feature vector to
produce perturbed feature vectors. The perturbed feature vectors are
converted into phonetic voice tag variants. A second utterance is then
recognized from the phonetic voice tag variants. See generally Abstract.
Claim 20 is reproduced below with the key disputed limitation
emphasized:
20. A method for producing phonetic voice tag variants in voice-
to-phoneme conversion comprising:
generating a feature vector from a first spoken utterance;
generating a first phonetic voice tag from said feature vector;
applying one or more perturbations to said feature vector for
producing one or more perturbed feature vectors;
converting said perturbed feature vectors into one or more phonetic
voice tag variants; and
recognizing a second spoken utterance from said one or more
phonetic voice tag variants and said first phonetic voice tag,
wherein a phonetic voice tag is a string of symbolic characters
representing phonemes of speech.
The Examiner relies on the following as evidence of unpatentability:
Steve Young et al., THE HTK BOOK (3d rev. 2000).
Yongwon Jeong & Hyung Soon Kim, Recognition Confidence
Scoring Using Recognition Results from Perturbed Input Feature Vectors,
37 ELECS. LETTERS 1143 (2001).
Yan Ming Cheng et al., Voice-to-Phoneme Conversion Algorithms for
Speaker-Independent Voice-Tag Applications in Embedded Platforms, 2005
IEEE WORKSHOP ON AUTOMATIC SPEECH RECOGNITION & UNDERSTANDING
403 (2005).
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The Rejections
1. The Examiner rejected claim 20 under 35 U.S.C. § 103(a) as
unpatentable over Cheng in view of Jeong. Ans. 4-7.
2. The Examiner rejected claim 20 under 35 U.S.C. § 103(a) as
unpatentable over Young in view of Jeong. Ans. 7-9.

The First Rejection (Cheng in view of Jeong)
The Examiner finds that Cheng in the left column of page 407 shows
the step of generating a feature vector from a first utterance, and finds that
Cheng in the right column of page 404 teaches generating a first phonetic
voice tag from the feature vector. Ans. 5. The Examiner further finds that
Cheng’s Table 2 on page 408 shows that a phonetic voice tag is a string of
symbolic characters representing phonemes of speech. Id. The Examiner
acknowledges that Cheng fails to show the steps of applying perturbations,
converting the perturbed feature vectors to generate phonetic voice tag
variants, and recognizing a second utterance from one or more voice tag
variants. Id. The Examiner then finds that Jeong shows these steps, citing
Jeong in the left column of page 1144 as showing three different methods for
applying perturbations to feature vectors. Ans. 5-6. The Examiner cites
Jeong in the right column of page 1144 as showing converting the perturbed
feature vectors into phonetic voice tag variants, and as showing recognizing
a second utterance from the phonetic voice tag variants. Ans. 6. The
Examiner asserts that there is motivation to combine Cheng and Jeong
because they are in similar fields (voice recognition) and Jeong’s Abstract
suggests its utility for improving out-of-vocabulary rejection. Ans. 7.
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The Second Rejection (Young in view of Jeong)
The Examiner finds that Young shows generating a feature vector at
page 28, section 3.1.5, and shows generating a first voice tag at page 29,
section 3.2. Ans. 7. The Examiner further points to Young at page 9, section
1.5, as teaching recognizing an utterance from one or more voice tags. Ans.
8. The Examiner acknowledges that Young fails to show applying
perturbations or converting the perturbed feature vectors into phonetic tag
variants. Id. The Examiner then finds that Jeong shows these steps, citing
portions of Jeong as above in the first rejection. Ans. 7-9.
Appellant argues, with respect to both rejections, that Jeong fails to
show the recited step of recognizing a second utterance from phonetic voice
tag variants and the voice tag generated from the first utterance. Appellant
appears to emphasize that Jeong fails to show anything comparable to
recognizing a second utterance from the combination of a voice tag of a first
utterance and voice tag variants generated from perturbations of the feature
vector of the first utterance. See Br. 8. More specifically, Appellant suggests
that: “Jeong uses the voice-tag variants of the first spoken utterance in order
to improve the recognition rate of the first spoken utterance. In Jeong, there
is nothing comparable to the second spoken utterance of the presently
pending claim 20.” Br. 8.

ISSUE
Under § 103, has the Examiner erred by finding that the cited prior art
collectively teaches or suggests recognizing a second spoken utterance from
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one or more phonetic voice tag variants and a first phonetic voice tag in
rejecting claim 20 over Cheng and Jeong or over Young and Jeong?

ANALYSIS
First Rejection (Cheng in view of Jeong)
Based on the record before us, we find no error in the Examiner’s
rejection of claim 20. As regards the disputed limitation (recognizing a
second utterance), the Examiner cites Jeong on the right column of page
1144 as showing the recognition of 800 utterances (test data) based on
perturbed voice tag variants (perturbations of feature vectors of training
data). Ans. 6. In response to Appellant’s arguments, the Examiner further
clarifies that Jeong shows using the training data (Jeong, p. 1144, left
column) as the recited “first utterance” and perturbations thereof to
recognize the test data (Jeong, p. 1144, right col., including Figure 1 test
results) as the second utterance. Ans. 9-10. The Examiner further clarifies
that although Jeong speaks of “feature vector” data, Cheng makes clear that
conversion between feature vector representations of an utterance and a
voice tag or phoneme string representation of an utterance is well known to
those of ordinary skill in the art. Ans. 10.
We agree with the Examiner’s finding that the training data of Jeong
corresponds to the recited first utterance. Specifically, in the right column of
page 1144, Jeong states: “For training, we used the Korean phonetically
optimized words (POW) speech database [4]. The size of the vocabulary is
3848 words spoken by 40 male speakers” (brackets in original). Jeong
further states: “Twelve mel-frequency cepstral coefficients (MFCC) and
their derivatives were used as feature vectors.” Id. Thus, the training
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database of Jeong comprises a first utterance, and Jeong generates a feature
vector from such a first utterance. Jeong further shows that the feature vector
is perturbed when in the left column of page 1144 the reference states:
“Therefore, the recognition result from perturbed input feature vectors can
be employed to improve the robustness of the confidence score. . . . [T]hree
different methods were tried for perturbing input feature vectors.” Thus,
Jeong teaches applying perturbations to produce perturbed feature vectors.
Returning to the right column of page 1144 of Jeong, it is further clear that
using the training data and one or more perturbations of a first utterance in
that training data improves recognition of words in test data (second
utterances). Thus, Jeong teaches the recited features except for conversion
from a feature vector to a first phonetic voice tag and conversion from a
perturbed feature vector to a phonetic voice tag variant. Appellant has not
disputed that these features are taught by the art. Regardless, we find that
Cheng teaches that such conversions are well known to those of ordinary
skill in the art of voice recognition. For example, Cheng’s Abstract on page
403 recites (emphasis added):
In the first approach, a voice-to-phoneme conversion in batch
mode manages this task by preserving the commonality of input
feature vectors of multiple voice-tag example utterances. Given
multiple example utterances, a developed feature combination
strategy produces an “average” utterance, which is converted
to phonetic strings as a voice-tag representation via a speaker-
independent phonetic decoder.
Cheng therefore teaches the recited steps of conversion from a feature
vector to a voice tag. We therefore find that Appellant has not persuasively
rebutted the Examiner’s finding that Cheng and Jeong collectively teach all
the elements of claim 20, and we therefore affirm the Examiner’s rejection.
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For the foregoing reasons, Appellant has not persuaded us of error in
the rejection of claim 20 over Cheng and Jeong.

Second Rejection (Young in view of Jeong)
The Examiner rejected claim 20 over Young in view of Jeong in a
manner similar to the rejection over Cheng in view of Jeong. We note that in
this second rejection, the Examiner does not specifically cite in the prior art
recognition of a second utterance from the voice tag and voice tag variants
generated from a first utterance. Rather, the Examiner generally notes
Young at page 9, section 1.5, as showing recognizing an utterance from
voice tag information. We deem this error harmless for the Examiner made
clear in the first rejection (Cheng in view of Jeong) that Jeong teaches
recognizing a second utterance (test data) from the feature vector and the
perturbed feature vectors generated from a first utterance (training data).
Further, as noted above in the Examiner’s response to arguments, it was
clarified that Jeong shows essentially every element of claim 20. Ans. 9. The
Examiner further clarifies reliance on either Cheng or Young for showing
that it is known to convert from a feature vector (or perturbed feature vector)
into a corresponding voice tag.
We therefore find that Appellant has not persuasively rebutted the
Examiner’s finding that Young and Jeong collectively teach or suggest all
the elements of claim 20. We therefore sustain the Examiner’s rejection.
For the foregoing reasons, Appellant has not persuaded us of error in
the rejection of claim 20 over Young and Jeong.

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CONCLUSION
The Examiner has not erred in finding that the cited prior art
collectively teaches or suggests recognizing a second spoken utterance from
one or more phonetic voice tag variants and a first phonetic voice tag. Thus,
the Examiner has not erred in rejecting claim 20 over Cheng and Jeong or
over Young and Jeong.

DECISION
The Examiner’s decision rejecting claim 20 is affirmed.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv).

AFFIRMED

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