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US Patent 10943583 Creation of language models for speech recognition

Patent 10943583 was granted and assigned to Amazon on March, 2021 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
Amazon
Amazon
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Current Assignee
Amazon
Amazon
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
109435830
Patent Inventor Names
Ariya Rastrow0
Shaswat Pratap Shah0
Ankur Gandhe0
Date of Patent
March 9, 2021
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Patent Application Number
159338380
Date Filed
March 23, 2018
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Patent Citations
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US Patent 10192552 Digital assistant providing whispered speech
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US Patent 10217452 Speech synthesis device and method
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US Patent 10276149 Dynamic text-to-speech output
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US Patent 10319250 Pronunciation guided by automatic speech recognition
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US Patent 10339925 Generation of automated message responses
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US Patent 10319365 Text-to-speech processing with emphasized output audio
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US Patent 10388272 Training speech recognition systems using word sequences
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US Patent 10448115 Speech recognition for localized content
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Patent Citations Received
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US Patent 12125473 Speech recognition method, apparatus, and device, and storage medium
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US Patent 11544461 Early exit for natural language processing models
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US Patent 11562747 Speech-to-text transcription with multiple languages
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US Patent 11880658 Method and system for implementing a natural language interface to data stores using deep learning
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US Patent 11887620 Language model score calculation apparatus, language model generation apparatus, methods therefor, program, and recording medium
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US Patent 11935517 Speech decoding method and apparatus, computer device, and storage medium
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US Patent 12008479 Automatic determination of the run parameters for a software application on an information processing platform by genetic algorithm and enhanced noise management
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US Patent 12079579 Intention identification model learning method, apparatus, and device
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Patent Primary Examiner
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Mohammad K Islam
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Patent abstract

A system to perform automatic speech recognition (ASR) using a dynamic language model. Portions of the language model can include a group of probabilities rather than a single probability. At runtime individual probabilities of the group are weighted and combined to create an adjusted probability for the portion of the language model. The adjusted probability can be used for ASR processing. The weights can be determined based on a characteristic of the utterance, for example an associated speechlet/application, the specific user speaking, or other characteristic. By applying the weights at runtime the system can use a single language model to dynamically adjust to different utterance conditions.

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