US6006182A
Expired / Lapsed
US
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Speech recognition rejection method using generalized additive models
Assignee: RPX Clearinghouse LLC
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Filing: 1997-09-22
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Granted: 1999-12-21
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Expires: 2017-09-22
Abstract
Abstract Systems and methods consistent with the present invention determine whether to accept one of a plurality of intermediate recognition results output by a speech recognition system as a final recognition result. The system first combines a plurality of speech rejection features into a feature function in which weights are assigned to each rejection feature in accordance with a recognition accuracy of each rejection feature. Feature values are then calculated for each of the rejection features using the plurality of intermediate recognition results. The system next computes the feature function according to the calculated feature values to determine a rejection decision value. Finally, one of the plurality of intermediate recognition results is accepted as the final recognition result according to the rejection decision value.
Inventors
- 👤 Waleed Fakhr
- 👤 Serge Robillard
- 👤 Vishwa Gupta
- 👤 Real Tremblay
- 👤 Michael Sabourin
- 👤 Jean-Francois Crespo
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 11:37
CPC Classifications
G; G10; G10L; G10L15/00; G10L15/08; G10L15/14; G10L15/142
Claims Analysis
Total Claims: 31
Claim 1
Independent Claim
118 words
A computer-implemented method for accepting one of a plurality of intermediate recognition results output by a speech recognition system as a final recognition result, the method comprising the steps of: combining a plurality of speech rejection features into a generalized additive model (GAM) feature function in which weights are assigned to each rejection feature in accordance with a recognition accuracy of each rejection feature; calculating feature values for each of the rejection features using the plurality of intermediate recognition results; computing the GAM feature function according to the calculated feature values to determine a rejection decision value; and accepting one of the plurality of intermediate recognition results as the final recognition result according to the rejection decision value.
Claim 2
Dependent Claim
118 words
A computer-implemented method for accepting one of a plurality of intermediate recognition results output by a speech recognition system as a final recognition result, the method comprising the steps of: combining a plurality of speech rejection features into a generalized additive model (GAM) feature function in which weights are assigned to each rejection feature in accordance with a recognition accuracy of each rejection feature; calculating feature values for each of the rejection features using the plurality of intermediate recognition results; computing the GAM feature function according to the calculated feature values to determine a rejection decision value; and accepting one of the plurality of intermediate recognition results as the final recognition result according to the rejection decision value.
Claim 3
Dependent Claim
38 words
The method of claim 1, wherein the GAM feature function includes a plurality of coefficients, and wherein the method further includes the step of: using a speech training set to determine the coefficients of the GAM feature function.
Claim 4
Dependent Claim
66 words
The method of claim 1, wherein the feature function is defined by the following equation: ##EQU2## where: θ represents an offset value; δ represents a weight; F(f,α) represents a function describing each rejection feature f; J represents the number of rejection features that are combined in the equation for R(f); K represents the order of function F; and R(f) ranges in value from 0 to 1.
Claim 5
Dependent Claim
27 words
The method of claim 3, wherein the function F(f j ,α) describing each rejection feature is defined by the following equation: F(f.sub.i,α)=α.sub.i.1 f.sub.i +α.sub.i.2 f.sub.i.sup.2 +α.sub.i.3 f.sub.i.sup.3.
Claim 6
Dependent Claim
55 words
The method of claim 3, wherein the function F(f j ,α) is a polynomial having an order K and wherein the combining step further includes the substep of: measuring a modeling error produced by the feature function for a plurality of values for K; and selecting the order K according to the measured modeling error.
Claim 7
Dependent Claim
21 words
The method of claim 3, wherein the a coefficients for each rejection feature are determined using a gradient logistic regression method.
Claim 8
Dependent Claim
54 words
The method of claim 1, wherein the rejection features are any one of the following rejection features: (1) a score-per-frame feature; (2) a score ratio feature; (3) a score spread feature; (4) a normalized score difference feature; (5) a allophone number feature; (6) a confusability feature; and (7) the weighted Levinstein distance between words.
Claim 9
Dependent Claim
64 words
The method of claim 1, wherein the step of accepting one of the plurality of intermediate recognition results as the final recognition result further includes the substeps of: comparing the rejection decision value to a threshold value; and accepting one of the plurality of intermediate recognition results as the final recognition result according to whether the rejection decision value is above the threshold value.
Claim 10
Dependent Claim
61 words
The method of claim 1, wherein the plurality of intermediate recognition results are ranked according to a recognition score associated with each intermediate recognition result, and wherein the step of accepting one of the plurality of intermediate recognition results as the final recognition result further includes the substep of: accepting the top ranked intermediate recognition result as the final recognition result.
Claim 11
Independent Claim
122 words
A system for accepting one of a plurality of intermediate recognition results output by a speech recognition system as a final recognition result, the system comprising: means for combining a plurality of speech rejection features into a generalized additive model (GAM) feature function in which weights are assigned to each rejection feature in accordance with a recognition accuracy of each rejection feature; means for calculating feature values for each of the rejection features using the plurality of intermediate recognition results; means for computing the GAM feature function according to the calculated feature values to determine a rejection decision value; and means for accepting one of the plurality of intermediate recognition results as the final recognition result according to the rejection decision value.
Claim 12
Independent Claim
122 words
A system for accepting one of a plurality of intermediate recognition results output by a speech recognition system as a final recognition result, the system comprising: means for combining a plurality of speech rejection features into a generalized additive model (GAM) feature function in which weights are assigned to each rejection feature in accordance with a recognition accuracy of each rejection feature; means for calculating feature values for each of the rejection features using the plurality of intermediate recognition results; means for computing the GAM feature function according to the calculated feature values to determine a rejection decision value; and means for accepting one of the plurality of intermediate recognition results as the final recognition result according to the rejection decision value.
Claim 13
Dependent Claim
14 words
The system of claim 10, wherein coefficients of the GAM feature function are predetermined.
Claim 14
Dependent Claim
66 words
The system of claim 10, wherein the feature function is defined by the following equation: ##EQU3## where: θ represents an offset value; δ represents a weight; F(f,α) represents a function describing each rejection feature f; J represents the number of rejection features that are combined in the equation for R(f); K represents the order of function F; and R(f) ranges in value from 0 to 1.
Claim 15
Dependent Claim
27 words
The system of claim 12, wherein the function F(f j ,α) describing each rejection feature is defined by the following equation: F(f.sub.i,α)=α.sub.i.1 f.sub.i +α.sub.i.2 f.sub.i.sup.2 +α.sub.i.3 f.sub.i.sup.3.
Claim 16
Dependent Claim
57 words
The system of claim 12, wherein the function F(f j ,α) is a polynomial having an order K and wherein the means for combining further includes: means for measuring a modeling error produced by the feature function for a plurality of values for K; and means for selecting the order K according to the measured modeling error.
Claim 17
Dependent Claim
28 words
The system of claim 12, wherein the means for combining further includes: means for determining the a coefficients for each rejection feature using a gradient logistic regression method.
Claim 18
Dependent Claim
54 words
The system of claim 10, wherein the rejection features are any one of the following rejection features: (1) a score-per-frame feature; (2) a score ratio feature; (3) a score spread feature; (4) a normalized score difference feature; (5) a allophone number feature; (6) a confusability feature; and (7) the weighted Levinstein distance between words.
Claim 19
Dependent Claim
65 words
The system of claim 10, wherein the means for accepting one of the plurality of intermediate recognition results as the final recognition result further includes: means for comparing the rejection decision value to a threshold value; and means for accepting one of the plurality of intermediate recognition results as the final recognition result according to whether the rejection decision value is above the threshold value.
Claim 20
Dependent Claim
60 words
The system of claim 10, wherein the plurality of intermediate recognition results are ranked according to a recognition score associated with each intermediate recognition result, and wherein the means for accepting one of the plurality of intermediate recognition results as the final recognition result further includes: means for accepting the top ranked intermediate recognition result as the final recognition result.
Claim 21
Dependent Claim
16 words
The system of claim 10, wherein the speech recognition system is a voice activated dialing system.
Claim 22
Dependent Claim
136 words
A computer program product containing instructions for causing a computer to execute a method for accepting one of a plurality of intermediate recognition results output by a speech recognition system as a final recognition result, the computer program product comprising: instructions for combining a plurality of speech rejection features into a generalized additive model (GAM) feature function in which weights are assigned to each rejection feature in accordance with a recognition accuracy of each rejection feature; instructions for calculating feature values for each of the rejection features using the plurality of intermediate recognition results; instructions for computing the GAM feature function according to the calculated feature values to determine a rejection decision value; and instructions for accepting one of the plurality of intermediate recognition results as the final recognition result according to the rejection decision value.
Claim 23
Dependent Claim
136 words
A computer program product containing instructions for causing a computer to execute a method for accepting one of a plurality of intermediate recognition results output by a speech recognition system as a final recognition result, the computer program product comprising: instructions for combining a plurality of speech rejection features into a generalized additive model (GAM) feature function in which weights are assigned to each rejection feature in accordance with a recognition accuracy of each rejection feature; instructions for calculating feature values for each of the rejection features using the plurality of intermediate recognition results; instructions for computing the GAM feature function according to the calculated feature values to determine a rejection decision value; and instructions for accepting one of the plurality of intermediate recognition results as the final recognition result according to the rejection decision value.
Claim 24
Dependent Claim
68 words
The computer program product of claim 20, wherein the feature function is defined by the following equation: ##EQU4## where: θ represents an offset value; δ represents a weight; F(f,α) represents a function describing each rejection feature f; J represents the number of rejection features that are combined in the equation for R(f); K represents the order of function F; and R(f) ranges in value from 0 to 1.
Claim 25
Dependent Claim
29 words
The computer program product of claim 21, wherein the function F(f j ,α) describing each rejection feature is defined by the following equation: F(f.sub.j,α)=α.sub.j,1 f.sub.j +α.sub.j,2 f.sub.j.sup.2 +α.sub.j,3 f.sub.j.sup.3.
Claim 26
Dependent Claim
58 words
The computer program product of claim 21, wherein the function F(f j ,α) is a polynomial having an order K and wherein the combining instructions further includes: instructions for measuring a modeling error produced by the feature function for a plurality of values for K; and instructions for selecting the order K according to the measured modeling error.
Claim 27
Dependent Claim
23 words
The computer program product of claim 21, wherein the a coefficients for each rejection feature are determined using a gradient logistic regression method.
Claim 28
Dependent Claim
56 words
The computer program product of claim 20, wherein the rejection features are any one of the following rejection features: (1) a score-per-frame feature; (2) a score ratio feature; (3) a score spread feature; (4) a normalized score difference feature; (5) a allophone number feature; (6) a confusability feature; and (7) the weighted Levinstein distance between words.
Claim 29
Dependent Claim
67 words
The computer program product of claim 20, wherein the instructions for accepting one of the plurality of intermediate recognition results as the final recognition result further includes: instructions for comparing the rejection decision value to a threshold value; and instructions for accepting one of the plurality of intermediate recognition results as the final recognition result according to whether the rejection decision value is above the threshold value.
Claim 30
Dependent Claim
62 words
The computer program product of claim 20, wherein the plurality of intermediate recognition results are ranked according to a recognition score associated with each intermediate recognition result, and wherein the instructions for accepting one of the plurality of intermediate recognition results as the final recognition result further includes: instructions for accepting the top ranked intermediate recognition result as the final recognition result.
Claim 31
Dependent Claim
16 words
The computer program product of claim 20, wherein coefficients of the GAM feature function are predetermined.
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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) | 2002-12-20 | 2003-06-21 | 2003-12-21 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2006-12-20 | 2007-06-21 | 2007-12-21 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2010-12-20 | 2011-06-21 | 2011-12-21 | $7700.00 | Window Closed / Lapsed |