公开(公告)号：US09886946B2

公开(公告)日：2018-02-06

申请号：US15263714

申请日：2016-09-13

Applicant: Google Inc.

Inventor： Pedro J. Moreno-Mengibar ,  Petar Aleksic

IPC: G10L15/06 ,  G10L15/00 ,  G10L15/07 ,  G10L15/197 ,  G10L15/183 ,  G10L15/24

CPC classification number: G10L15/07 ,  G10L15/183 ,  G10L15/197 ,  G10L15/24

Abstract: 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).

公开(公告)号：US20160379625A1

公开(公告)日：2016-12-29

申请号：US15263714

申请日：2016-09-13

Applicant: Google Inc.

Inventor： Pedro J. Moreno-Mengibar ,  Petar Aleksic

IPC: G10L15/07 ,  G10L15/24 ,  G10L15/183

CPC classification number: G10L15/07 ,  G10L15/183 ,  G10L15/197 ,  G10L15/24

Abstract: 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).