Method of optimizing a composite speech recognition expert
First Claim
1. The method of adjusting the relative weighting coefficients to be applied to respective scores generated in a continuous speech recognizer which incorporates plural experts including at least an acoustic expert and a linguistic expert, the acoustic and linguistic experts generating respective scores for each work postulated from the system'"'"'s vocabulary;
- said method comprising;
obtaining continuous speech training data utilizing the words to be recognized in multiple word phrases;
submitting said multiple word phrases to at least one acoustic expert thereby to determine, for each such phrase, plural multi-word hypotheses each having a corresponding cumulative acoustic score denoting likelihood of match;
submitting said hypotheses to at least one linguistic expert thereby to determine for each hypothesis a corresponding cumulative linguistic score denoting likelihood of match;
for each hypothesis, combining said acoustic and linguistic cumulative scores using weighting coefficients initially arbitrarily selected thereby to obtain a respective combined hypothesis score;
for each submitted multiple work phrase, determining if any hypothesis is correct and, if a correct hypothesis exists,identifying the hypothesis which has the best combined score of those hypotheses which are not the correct hypothesiscomputing an objective function having a value which is variable as a function of a difference calculated between the combined score of the correct hypothesis and the combined score of said identified incorrect hypothesis;
cumulating the objective function values over all phrases which produced at least one correct hypothesis; and
calculating a vector direction of adjustment of said relative weighting coefficients which improves the cumulated objective function values; and
making an adjustment of said relative weighting coefficients in that direction.
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Abstract
In a continuous speech recognizer which includes at least, one acoustic expert and one linguistic expert which generate respective scores, a method is disclosed for adjusting the relative weighting to be applied to those scores employing training data utilizing the words to be recognized in multiple word phrases. Multiple word test phrases are applied to the acoustic expert to determine, for each phrase, plural multi-word hypotheses each having corresponding cumulative scores. The linguistic expert generates corresponding cumulative linguistic scores. An objective function is calculated for each test phrase having a value which is variable as a function of the difference between the combined score of any correct hypothesis and that of the most easily confused incorrect hypothesis. The objective function values are cumulated and a gradient descent procedure is used to adjust the relative weighting of the acoustic and linguistic scores in obtaining a combined score.
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Citations
7 Claims
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1. The method of adjusting the relative weighting coefficients to be applied to respective scores generated in a continuous speech recognizer which incorporates plural experts including at least an acoustic expert and a linguistic expert, the acoustic and linguistic experts generating respective scores for each work postulated from the system'"'"'s vocabulary;
- said method comprising;
obtaining continuous speech training data utilizing the words to be recognized in multiple word phrases; submitting said multiple word phrases to at least one acoustic expert thereby to determine, for each such phrase, plural multi-word hypotheses each having a corresponding cumulative acoustic score denoting likelihood of match; submitting said hypotheses to at least one linguistic expert thereby to determine for each hypothesis a corresponding cumulative linguistic score denoting likelihood of match; for each hypothesis, combining said acoustic and linguistic cumulative scores using weighting coefficients initially arbitrarily selected thereby to obtain a respective combined hypothesis score; for each submitted multiple work phrase, determining if any hypothesis is correct and, if a correct hypothesis exists, identifying the hypothesis which has the best combined score of those hypotheses which are not the correct hypothesis computing an objective function having a value which is variable as a function of a difference calculated between the combined score of the correct hypothesis and the combined score of said identified incorrect hypothesis; cumulating the objective function values over all phrases which produced at least one correct hypothesis; and calculating a vector direction of adjustment of said relative weighting coefficients which improves the cumulated objective function values; and making an adjustment of said relative weighting coefficients in that direction. - View Dependent Claims (2, 3, 4, 5)
- said method comprising;
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6. The method of adjusting the relative weighting coefficients to be applied to respective scores generated in a continuous speech recognizer which incorporates plural experts including at least an acoustic expert and a linguistic expert, the acoustic and linguistic experts generating respective scores for each word postulated from the system'"'"'s vocabulary;
- said method comprising;
obtaining continuous speech training data utilizing the words to be recognized in multiple word phrases; a) submitting said multiple work phrases to at least one acoustic expert thereby to determine, for each such phrase, plural multi-work hypotheses each having a corresponding cumulative acoustic score denoting likelihood of match; b) submitting said hypotheses to at least one linguistic expert thereby to determine for each hypothesis a corresponding cumulative linguistic score denoting likelihood of match c) for each hypothesis, combining said acoustic and linguistic cumulative scores using weighting coefficients initially arbitrarily selected thereby to obtain a respective combined hypothesis score; d) for each submitted phrase, determining if any hypothesis is correct and, if a correct hypothesis exists, computing an objective function having a value which is variable as a function of a difference calculated between the combined score of the correct hypothesis and the combined score of the hypothesis which has the best score of those hypotheses which are not the correct hypothesis; e) cumulating the objective function values over all phrases which produced at least one correct hypothesis; and f) calculating a vector direction of adjustment of said coefficients which improves the cumulated objective function values; g) making an adjustment of said coefficients in said direction; and repeating steps a)-g) at least once.
- said method comprising;
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7. The method of adjusting the relative weighting coefficients to be applied to respective scores generated in a continuous speech recognizer which incorporates plural experts including at least an acoustic expert and a linguistic expert, the acoustic and linguistic experts generating respective scores for each work postulated from the system'"'"'s vocabulary;
- said method comprising;
obtaining continuous speech training data utilizing the words to be recognized in multiple word phrases; submitting said multiple word phrases to at least one acoustic expert thereby to determine, for each such phrase, plural multi-word hypotheses each having a corresponding cumulative acoustic score denoting likelihood of match; submitting said hypotheses to at least one linguistic expert thereby to determine for each hypothesis a corresponding cumulative linguistic score denoting likelihood of match; for each hypothesis, combining said acoustic and linguistic cumulative scores using weighting coefficients initially arbitrarily selected thereby to obtain a respective combined hypothesis score; for each submitted multiple work phrase, determining if any hypothesis is correct and, if a correct hypothesis exists, identifying the hypothesis which has the best combined score of those hypotheses which are not the correct hypothesis between the combined score of the correct hypothesis and the combined score of said identified incorrect hypothesis; adjusting said difference in accordance with a sigmoidal function ##EQU11## where x is the respective difference computing an objective function having a value which is variable as a function of the adjusted difference calculating a difference cumulating the objective function values over all phrases which produced at least one correct hypothesis; and calculating a vector direction of adjustment of said relative weighting coefficients which improved the cumulated objective function values; and making an adjustment of said relative weighting coefficients in that direction.
- said method comprising;
Specification