Speaker and call characteristic sensitive open voice search
First Claim
1. A method comprising:
- classifying, by a computing device, speech into at least one voice cluster based on identified acoustic features of the speech, the at least one voice cluster corresponding to a text cluster and a customized language model that reflects characteristics of a speaker of the speech;
determining, by the computing device, a text query based on the customized language model and one or more text strings determined based on the speech;
receiving, by the computing device, search results based on the text query, each of the search results having a ranking indicating a measure of importance relative to other of the search results; and
re-ranking, by the computing device, the search results based on re-scoring the search results using the text cluster;
receiving a user interaction log comprising click data associated with a user interaction with the re-ranked search results;
updating the at least one voice cluster based on the user interaction with the re-ranked search results; and
updating the customized language model based on the click data associated with the user interaction with the re-ranked search results.
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Abstract
Techniques disclosed herein include systems and methods for open-domain voice-enabled searching that is speaker sensitive. Techniques include using speech information, speaker information, and information associated with a spoken query to enhance open voice search results. This includes integrating a textual index with a voice index to support the entire search cycle. Given a voice query, the system can execute two matching processes simultaneously. This can include a text matching process based on the output of speech recognition, as well as a voice matching process based on characteristics of a caller or user voicing a query. Characteristics of the caller can include output of voice feature extraction and metadata about the call. The system clusters callers according to these characteristics. The system can use specific voice and text clusters to modify speech recognition results, as well as modifying search results.
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Citations
16 Claims
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1. A method comprising:
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classifying, by a computing device, speech into at least one voice cluster based on identified acoustic features of the speech, the at least one voice cluster corresponding to a text cluster and a customized language model that reflects characteristics of a speaker of the speech; determining, by the computing device, a text query based on the customized language model and one or more text strings determined based on the speech; receiving, by the computing device, search results based on the text query, each of the search results having a ranking indicating a measure of importance relative to other of the search results; and re-ranking, by the computing device, the search results based on re-scoring the search results using the text cluster; receiving a user interaction log comprising click data associated with a user interaction with the re-ranked search results; updating the at least one voice cluster based on the user interaction with the re-ranked search results; and updating the customized language model based on the click data associated with the user interaction with the re-ranked search results. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. Non-transitory computer-readable media storing executable instructions that, when executed by one or more processors, cause a system to:
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classify speech into at least one voice cluster based on identified acoustic features of the speech, the at least one voice cluster corresponding to a text cluster and a customized language model that reflects characteristics of a speaker of the speech; determine a text query based on the customized language model and one or more text strings determined based on the speech; receive search results based on the text query, each of the search results having a ranking indicating a measure of importance relative to other of the search results; re-rank the search results based on re-scoring the search results using the text cluster; receive a user interaction log comprising click data associated with a user interaction with the re-ranked search results; update the at least one voice cluster based on the user interaction with the re-ranked search results; and update the customized language model based on the click data associated with the user interaction with the re-ranked search results. - View Dependent Claims (15, 16)
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12. A system comprising:
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one or more processors; and non-transitory memory storing executable instructions that, when executed by the one or more processors, cause the system to; classify speech into at least one voice cluster based on identified acoustic features of the speech, the at least one voice cluster corresponding to a text cluster and a customized language model that reflects characteristics of a speaker of the speech; determine a text query based on the customized language model and one or more text strings determined based on the speech; receive search results based on the text query, each of the search results having a ranking indicating a measure of importance relative to other of the search results; re-rank the search results based on re-scoring the search results using the text cluster; receive a user interaction log comprising click data associated with a user interaction with the re-rank search results; update the at least one voice cluster based on the user interaction with the re-ranked search results; and update the customized language model based on the click data associated with the user interaction with the re-ranked search results. - View Dependent Claims (13, 14)
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Specification