发明名称 Language model biasing modulation
摘要 Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for modulating language model biasing. In some implementations, context data is received. A likely context associated with a user is determined based on at least a portion of the context data. One or more language model biasing parameters based at least on the likely context associated with the user is selected. A context confidence score associated with the likely context based on at least a portion of the context data is determined. One or more language model biasing parameters based at least on the context confidence score is adjusted. A baseline language model based at least on the one or more of the adjusted language model biasing parameters is biased. The baseline language model is provided for use by an automated speech recognizer (ASR).
申请公布号 US9460713(B1) 申请公布日期 2016.10.04
申请号 US201514673731 申请日期 2015.03.30
申请人 Google Inc. 发明人 Moreno Mengibar Pedro J.;Aleksic Petar
分类号 G10L15/00;G10L15/197;G10L15/08 主分类号 G10L15/00
代理机构 Fish & Richardson P.C. 代理人 Fish & Richardson P.C.
主权项 1. A computer-implemented method comprising: receiving audio data encoding an utterance of a user; receiving context data associated with the received audio data; determining a likely context associated with a user, based on at least a portion of the context data; selecting one or more language model biasing parameters based at least on the likely context associated with the user; determining a context confidence score associated with the likely context based on at least a portion of the context data, and additional context data indicating (i) that the user has switched between applications, (ii) a time difference between a presentation of a search result and a user response to the presentation of the search result, (iii) gaze tracking data, or (iv) a user behavior in response to visible content; adjusting one or more of the language model biasing parameters based at least on the context confidence score; biasing a baseline language model based at least on one or more of the adjusted language model biasing parameters; providing the biased language model for use by an automated speech recognizer (ASR); generating a transcription of the received audio data using the biased language model; and transmitting the generated transcription for display on a client computing device.
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