US5737489A
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Discriminative utterance verification for connected digits recognition
Assignee: Nokia of America Corp
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Filing: 1995-09-15
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Granted: 1998-04-07
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Expires: 2015-09-15
Abstract
Abstract In a speech recognition system, a recognition processor receives an unknown utterance signal as input. The recognition processor in response to the unknown utterance signal input accesses a recognition database and scores the utterance signal against recognition models in the recognition database to classify the unknown utterance and to generate a hypothesis speech signal. A verification processor receives the hypothesis speech signal as input to be verified. The verification processor accesses a verification database to test the hypothesis speech signal against verification models reflecting a preselected type of training stored in the verification database. Based on the verification test, the verification processor generates a confidence measure signal. The confidence measure signal can be compared against a verification threshold to determine the accuracy of the recognition decision made by the recognition processor.
Inventors
- 👤 Wu Chou
- 👤 Biing-Hwang Juang
- 👤 Chin-hui Lee
- 👤 Mazin G. Rahim
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-03 18:06
CPC Classifications
G; G10; G10L; G10L15/00; G10L15/08; G10L15/14; G10L15/142; G10L15/144; G10L15/06; G10L15/063; G10L15/10; G10L15/22; G10L2015/225
Claims Analysis
Total Claims: 22
Claim 1
Independent Claim
185 words
A speech signal processing method of making a speech recognizer verification model database based on one or more known hypothesis string signals representing known speech utterances and a set of current verification models, the method comprising the following steps: (A) receiving a known hypothesis string signal representing a known speech utterance; (B) generating a first string-based confidence measure signal based on the known hypothesis string signal representing a known speech utterance and a current verification model for that signal; (C) generating one or more other string-based confidence measure signals, each such string-based confidence measure signal based on the known hypothesis string signal representing a known speech utterance and another current verification model; (D) computing a misverification signal based on the first string-based confidence measure signal and the other string-based confidence measure signals; (E) based on the misverification signal and the known hypothesis string signal representing a known speech utterance, modifying one or more of the current verification models to decrease the likelihood of misverifying an unknown hypothesis string signal representing an unknown speech utterance; and (F) storing one or more modified verification models in memory.
Claim 2
Dependent Claim
185 words
A speech signal processing method of making a speech recognizer verification model database based on one or more known hypothesis string signals representing known speech utterances and a set of current verification models, the method comprising the following steps: (A) receiving a known hypothesis string signal representing a known speech utterance; (B) generating a first string-based confidence measure signal based on the known hypothesis string signal representing a known speech utterance and a current verification model for that signal; (C) generating one or more other string-based confidence measure signals, each such string-based confidence measure signal based on the known hypothesis string signal representing a known speech utterance and another current verification model; (D) computing a misverification signal based on the first string-based confidence measure signal and the other string-based confidence measure signals; (E) based on the misverification signal and the known hypothesis string signal representing a known speech utterance, modifying one or more of the current verification models to decrease the likelihood of misverifying an unknown hypothesis string signal representing an unknown speech utterance; and (F) storing one or more modified verification models in memory.
Claim 3
Dependent Claim
18 words
A method according to claim 1, further comprising the step: initializing the verification models in the verification database.
Claim 4
Dependent Claim
38 words
A method according to claim 1, further comprising the steps: computing a loss function signal based on the misverification signal; and determining a gradient of the loss function signal including calculating the derivative of the loss function signal.
Claim 5
Dependent Claim
47 words
A method according to claim 1, wherein step (B) comprises the steps: segmenting the known hypothesis string signal into a series of word signals; calculating a word-based confidence score for each word signal of the series; and averaging the word-based confidence scores calculated for each word signal.
Claim 6
Dependent Claim
70 words
A method according to claim 1, wherein step (C) comprises the steps: generating a set of confusable string models based on the known hypothesis string signal, a confusable string model comprising one or more word models; generating a string-based confidence measure signal for each of the set of confusable string models; and calculating an average of the string-based confidence measure signals for each of the set of confusable string models.
Claim 7
Dependent Claim
67 words
A method according to claim 5, wherein step (C) further comprises the steps: determining a word-based confidence score for each word model of each of the set of confusable string models; and averaging the word-based confidence scores determined for each word model of each of the set of confusable string model to generate the string-based confidence measure signal for each of the set of confusable string models.
Claim 8
Dependent Claim
62 words
A method according to claim 1, wherein step (D) comprises the step: determining a gradient of a function relating (a) confidence measure signal generation for the known hypothesis string signal based on a current verification model for that hypothesis string signal to (b) confidence measure signal generation for the known hypothesis string signal based on one or more other current verification models.
Claim 9
Dependent Claim
26 words
A method according to claim 7, wherein step (E) comprises the step: adjusting one or more parameters of the current verification models based on the gradient.
Claim 10
Dependent Claim
36 words
A method according to claim 1, wherein step (D) comprises the step: forming a difference between (a) the first string-based confidence measure signal and (b) an average of the one or more other confidence measure signals.
Claim 11
Dependent Claim
36 words
A method according to claim 3, further comprising the steps: estimating an expected loss function signal; and iteratively adjusting the verification models responsive to the estimated loss function signal to minimize the likelihood of verification error.
Claim 12
Dependent Claim
73 words
A speech recognition system for recognizing a string of connected spoken words, comprising: a recognition processor for generating a hypothesis string signal representing an unknown speech utterance responsive to an acoustic input string of connected spoken words; a recognition database for storing recognition models; a verification processor for generating a string-based confidence measure signal responsive to the hypothesis string signal representing an unknown speech utterance; and a verification database for storing verification models.
Claim 13
Dependent Claim
73 words
A speech recognition system for recognizing a string of connected spoken words, comprising: a recognition processor for generating a hypothesis string signal representing an unknown speech utterance responsive to an acoustic input string of connected spoken words; a recognition database for storing recognition models; a verification processor for generating a string-based confidence measure signal responsive to the hypothesis string signal representing an unknown speech utterance; and a verification database for storing verification models.
Claim 14
Dependent Claim
56 words
A speech recognition system according to claim 11, further comprising: means, coupled to the verification processor, for calculating a verification threshold signal value of a string-based confidence measure signal; means for measuring the string-based confidence measure signal to generate a measured signal value; and means for comparing the measured signal value to the threshold signal value.
Claim 15
Dependent Claim
20 words
A speech recognition system according to claim 11, wherein: the verification models comprise a set of hidden Markov model parameters.
Claim 16
Dependent Claim
29 words
A speech recognition system according to claim 11, wherein: the verification models are selected from the group consisting of keyword models, anti-keyword models, acoustic filler models, and combinations thereof.
Claim 17
Dependent Claim
15 words
A speech recognition system according to claim 11, wherein: the verification models reflect discriminative training.
Claim 18
Dependent Claim
66 words
A speech recognition system according to claim 11, wherein: the hypothesis string signal comprises a segmented series of word signals; and the verification processor comprises means for calculating a word-based confidence score for each word signal of the segmented series; and means for generating the string-based confidence measure signal responsive to an average of the word-based confidence scores for each word signal of the segmented series.
Claim 19
Dependent Claim
195 words
A speech signal processing method for generating a verification threshold signal sample of a confidence measure signal generated by a verification processor in a speech recognition system, comprising the following steps: (A) performing a round of operating the verification processor to (i) generate a first string-based confidence measure signal based on a known hypothesis string signal representing a known speech utterance and a current verification model for the known hypothesis string signal representing a known speech utterance, and (ii) generate one or more other string-based confidence measure signals, each such string-based confidence measure signal based on the known hypothesis string signal representing a known speech utterance and another verification model; (B) repeating step (A) for a preselected number of rounds; (C) recording a first distribution of first string-based confidence measure signal values for the preselected number of rounds; (D) recording a second distribution of the one or more other string-based confidence measure signal values for the preselected number of rounds; (E) calculating a first mean for the first distribution; (F) calculating a second mean for the second distribution; and (G) generating the verification threshold signal sample based on the first mean and the second mean.
Claim 20
Dependent Claim
195 words
A speech signal processing method for generating a verification threshold signal sample of a confidence measure signal generated by a verification processor in a speech recognition system, comprising the following steps: (A) performing a round of operating the verification processor to (i) generate a first string-based confidence measure signal based on a known hypothesis string signal representing a known speech utterance and a current verification model for the known hypothesis string signal representing a known speech utterance, and (ii) generate one or more other string-based confidence measure signals, each such string-based confidence measure signal based on the known hypothesis string signal representing a known speech utterance and another verification model; (B) repeating step (A) for a preselected number of rounds; (C) recording a first distribution of first string-based confidence measure signal values for the preselected number of rounds; (D) recording a second distribution of the one or more other string-based confidence measure signal values for the preselected number of rounds; (E) calculating a first mean for the first distribution; (F) calculating a second mean for the second distribution; and (G) generating the verification threshold signal sample based on the first mean and the second mean.
Claim 21
Dependent Claim
49 words
A method according to claim 17, further comprising the steps: selecting a false rejection verification error rate; selecting a false acceptance verification error rate; and estimating an initial verification threshold signal value based on the selected false rejection verification error rate and the selected false acceptance verification error rate.
Claim 22
Dependent Claim
44 words
A method according to claim 18, further comprising the steps: generating the verification threshold signal value while the speech recognition system is operating; and maintaining the false rejection verification error rate and the false acceptance verification error rate while the recognition system is operating.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2001-04-06 | 2001-10-06 | 2002-04-07 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2005-04-06 | 2005-10-06 | 2006-04-07 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2009-04-06 | 2009-10-06 | 2010-04-07 | $7700.00 | Window Closed / Lapsed |