System and method of speech recognition for non-native speakers of a language
First Claim
1. A method for speech recognition of input speech in a language from a non-native speaker, the method comprising acts of:
- generating one or more feature vectors based upon one or more voice-induced electrical signals that result from the input speech;
generating a first-language phoneme sequence from the one or more feature vectors based upon a first-language acoustic model, wherein the first-language acoustic model corresponds to a first language;
determining a second-language speech segment from the first-language phoneme sequence based upon a second-language lexicon model, wherein the second-language lexicon model corresponds to a second language that is different from the first language;
determining a confidence score associated with a combination of the first-language acoustic model and the second-language lexicon model; and
selecting the first-language acoustic model from a plurality of acoustic models based at least in part on the determined confidence score, each of the plurality of acoustic models corresponding to a different respective language.
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Abstract
An accent compensative speech recognition system and related methods for use with a signal processor generating one or more feature vectors based upon a voice-induced electrical signal are provided. The system includes a first-language acoustic module that determines a first-language phoneme sequence based upon one or more feature vectors, and a second-language lexicon module that determines a second-language speech segment based upon the first-language phoneme sequence. A method aspect includes the steps of generating a first-language phoneme sequence from at least one feature vector based upon a first-language phoneme model, and determining a second-language speech segment from the first-language phoneme sequence based upon a second-language lexicon model.
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Citations
18 Claims
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1. A method for speech recognition of input speech in a language from a non-native speaker, the method comprising acts of:
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generating one or more feature vectors based upon one or more voice-induced electrical signals that result from the input speech; generating a first-language phoneme sequence from the one or more feature vectors based upon a first-language acoustic model, wherein the first-language acoustic model corresponds to a first language; determining a second-language speech segment from the first-language phoneme sequence based upon a second-language lexicon model, wherein the second-language lexicon model corresponds to a second language that is different from the first language; determining a confidence score associated with a combination of the first-language acoustic model and the second-language lexicon model; and selecting the first-language acoustic model from a plurality of acoustic models based at least in part on the determined confidence score, each of the plurality of acoustic models corresponding to a different respective language. - View Dependent Claims (2, 3, 4, 5, 6)
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7. At least one computer-readable medium encoded with instructions that, when executed by at least one computer system, perform a method for speech recognition of input speech in a language from a non-native speaker, the method comprising acts of:
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generating, based upon a first-language acoustic model, a first-language phoneme sequence from one or more feature vectors, the one or more feature vectors being based upon one or more voice-induced electrical signals that result from the input speech, wherein the first-language acoustic model corresponds to a first language; determining a second-language speech segment from the first-language phoneme sequence based upon a second-language lexicon model, wherein the second-language lexicon model corresponds to a second language that is different from the first language; determining a confidence score associated with a combination of the first-language acoustic model and the second-language lexicon model; and selecting the first-language acoustic model from a plurality of acoustic models based at least in part on the determined confidence score, each of the plurality of acoustic models corresponding to a different respective language. - View Dependent Claims (8, 9, 10, 11, 12)
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13. An apparatus for speech recognition of input speech in a language from a non-native speaker, the apparatus comprising:
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at least one computer-readable medium encoded with instructions; and at least one processing unit coupled to the at least one computer-readable medium, wherein upon execution of the instructions by the at least one processing unit, the at least one processing unit; generates one or more feature vectors based upon one or more voice-induced electrical signals that result from the input speech; generates a first-language phoneme sequence from the one or more feature vectors based upon a first-language acoustic model, wherein the first-language acoustic model corresponds to a first language; determines a second-language speech segment from the first-language phoneme sequence based upon a second-language lexicon model, wherein the second-language lexicon model corresponds to a second language that is different from the first language; determines a confidence score associated with a combination of the first-language acoustic model and the second-language lexicon model; and selects the first-language acoustic model from a plurality of acoustic models based at least in part on the determined confidence score, each of the plurality of acoustic models corresponding to a different respective language. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification