Spoken utterance classification training for a speech recognition system
First Claim
1. In a computing environment, a method performed at least in part on at least one processor, comprising:
- receiving, by a speech recognition system, spoken utterances and associated confirmations;
processing, by a classifier of the speech recognition system, the spoken utterances and associated confirmations from output data associated with the speech recognition system, including for each spoken utterance having a denied confirmation, assigning a pseudo-semantic label that is a representation of an association between the denied confirmation and a rejected semantic label selected from a set of potential semantic labels, and updating a classification model associated with the classifier using each assigned pseudo-semantic label, wherein the denied confirmation comprises determining a negative response to a confirmation prompt delivered by the speech recognition system.
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Abstract
The subject disclosure is directed towards training a classifier for spoken utterances without relying on human-assistance. The spoken utterances may be related to a voice menu program for which a speech comprehension component interprets the spoken utterances into voice menu options. The speech comprehension component provides confirmations to some of the spoken utterances in order to accurately assign a semantic label. For each spoken utterance with a denied confirmation, the speech comprehension component automatically generates a pseudo-semantic label that is consistent with the denied confirmation and selected from a set of potential semantic labels and updates a classification model associated with the classifier using the pseudo-semantic label.
41 Citations
20 Claims
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1. In a computing environment, a method performed at least in part on at least one processor, comprising:
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receiving, by a speech recognition system, spoken utterances and associated confirmations; processing, by a classifier of the speech recognition system, the spoken utterances and associated confirmations from output data associated with the speech recognition system, including for each spoken utterance having a denied confirmation, assigning a pseudo-semantic label that is a representation of an association between the denied confirmation and a rejected semantic label selected from a set of potential semantic labels, and updating a classification model associated with the classifier using each assigned pseudo-semantic label, wherein the denied confirmation comprises determining a negative response to a confirmation prompt delivered by the speech recognition system. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. In a computing environment, a system, comprising:
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at least one processor; a memory coupled to the at least one processor; and a speech comprehension component implemented on the at least one processor and configured to receive spoken utterances, process the spoken utterances using a classifier, generate output data comprising settled semantic labels for at least a portion of the spoken utterances and one or more confirmations associated with one or more of the spoken utterances, and assign pseudo-semantic labels for at least another portion of the spoken utterances having denied confirmations using the output data generated, the pseudo-semantic labels comprising representations of an association between the denied confirmations and one or more rejected semantic labels, the speech comprehension component further configured to train a classification model associated with the classifier with the pseudo-semantic labels and the settled semantic labels, and to use the classification model to navigate a speaking entity to desired information. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A method comprising:
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receiving, by at least one processing device, a log file comprising data associated with one or more spoken utterances, system prompt information, and denied confirmations associated with a sub-set of the one or more spoken utterances; calculating pseudo-semantic labels for each spoken utterance in the sub-set of the one or more spoken utterances, the pseudo-semantic labels comprising a classification result that is consistent with both the data and the denied confirmations, is selected from a set of potential concepts germane to the data and the system prompt information, and represents an association between the denied confirmation and one or more rejected semantic labels; training a classifier using the calculated pseudo-semantic labels; and using the trained classifier to process input speech data. - View Dependent Claims (19, 20)
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Specification