DYNAMIC ADAPTATION OF LANGUAGE MODELS AND SEMANTIC TRACKING FOR AUTOMATIC SPEECH RECOGNITION
First Claim
1. A system for recognizing phrases of speech from a conversation, said system comprising:
- an automatic speech recognition (ASR) circuit to transcribe speech, of a user of said system, to a first estimated text sequence, based on a generalized language model;
a language model matching circuit to analyze said first estimated text sequence to determine a context and to select a personalized language model (PLM), from a plurality of PLMs, based on said context; and
said ASR circuit further to re-transcribe said speech based on said selected PLM to generate a lattice of paths of estimated text sequences, wherein each of said paths of estimated text sequences comprise one or more words and an acoustic score associated with each of said words.
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Abstract
Generally, this disclosure provides systems, devices, methods and computer readable media for adaptation of language models and semantic tracking to improve automatic speech recognition (ASR). A system for recognizing phrases of speech from a conversation may include an ASR circuit configured to transcribe a user'"'"'s speech to a first estimated text sequence, based on a generalized language model. The system may also include a language model matching circuit configured to analyze the first estimated text sequence to determine a context and to select a personalized language model (PLM), from a plurality of PLMs, based on that context. The ASR circuit may further be configured to re-transcribe the speech based on the selected PLM to generate a lattice of paths of estimated text sequences, wherein each of the paths of estimated text sequences comprise one or more words and an acoustic score associated with each of the words.
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Citations
27 Claims
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1. A system for recognizing phrases of speech from a conversation, said system comprising:
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an automatic speech recognition (ASR) circuit to transcribe speech, of a user of said system, to a first estimated text sequence, based on a generalized language model; a language model matching circuit to analyze said first estimated text sequence to determine a context and to select a personalized language model (PLM), from a plurality of PLMs, based on said context; and said ASR circuit further to re-transcribe said speech based on said selected PLM to generate a lattice of paths of estimated text sequences, wherein each of said paths of estimated text sequences comprise one or more words and an acoustic score associated with each of said words. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method for recognizing phrases of speech from a conversation, said method comprising:
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transcribing speech, of a participant in said conversation, to a first estimated text sequence, by an automatic speech recognition (ASR) circuit, said transcription based on a generalized language model; analyzing said first estimated text sequence to determine a context; selecting a personalized language model (PLM), from a plurality of PLMs, based on said context; and re-transcribing said speech, by said ASR circuit, based on said selected PLM, to generate a lattice of paths of estimated text sequences, wherein each of said paths of estimated text sequences comprise one or more words and an acoustic score associated with each of said words. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. At least one computer-readable storage medium having instructions stored thereon which when executed by a processor result in the following operations for recognizing phrases of speech from a conversation, said operations comprising:
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transcribing speech, of a participant in said conversation, to a first estimated text sequence, by an automatic speech recognition (ASR) circuit, said transcription based on a generalized language model; analyzing said first estimated text sequence to determine a context; selecting a personalized language model (PLM), from a plurality of PLMs, based on said context; and re-transcribing said speech, by said ASR circuit, based on said selected PLM, to generate a lattice of paths of estimated text sequences, wherein each of said paths of estimated text sequences comprise one or more words and an acoustic score associated with each of said words. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27)
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Specification