US6463413B1
Expired / Lapsed
US
⏱️ 0.0 years remaining
Speech recognition training for small hardware devices
Assignee: Panasonic Holdings Corp
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Filing: 1999-04-20
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Granted: 2002-10-08
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Expires: 2019-04-20
Abstract
Abstract A distributed speech processing system for constructing speech recognition reference models that are to be used by a speech recognizer in a small hardware device, such as a personal digital assistant or cellular telephone. The speech processing system includes a speech recognizer residing on a first computing device and a speech model server residing on a second computing device. The speech recognizer receives speech training data and processes it into an intermediate representation of the speech training data. The intermediate representation is then communicated to the speech model server. The speech model server generates a speech reference model by using the intermediate representation of the speech training data and then communicates the speech reference model back to the first computing device for storage in a lexicon associated with the speech recognizer.
Inventors
- 👤 Ted H. Applebaum
- 👤 Jean-claude Junqua
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 18:42
CPC Classifications
G; G10; G10L; G10L15/00; G10L15/28; G10L15/30; G10L15/06; G10L15/08; G10L15/18; G10L15/183; G10L15/187; G10L15/22; G10L15/063; G10L2015/0638
Claims Analysis
Total Claims: 36
Claim 1
Independent Claim
142 words
A speech processing system for constructing speech recognition reference models, comprising: a speech recognizer residing on a first computing device; said speech recognizer receiving speech training data and processing the speech training data into an intermediate representation of the speech training data, said speech recognizer further being operative to communicate the intermediate representation to a second computing device; a speech model server residing on said second computing device, said second computing device being interconnected via a network to said first computing device; said speech model server receiving the intermediate representation of the speech training data and generating a speech reference model using the intermediate representation, said speech model server further being operative to communicate the speech reference model to said first computing device; and a lexicon coupled to said speech recognizer for storing the speech reference model on said first computing device.
Claim 2
Dependent Claim
142 words
A speech processing system for constructing speech recognition reference models, comprising: a speech recognizer residing on a first computing device; said speech recognizer receiving speech training data and processing the speech training data into an intermediate representation of the speech training data, said speech recognizer further being operative to communicate the intermediate representation to a second computing device; a speech model server residing on said second computing device, said second computing device being interconnected via a network to said first computing device; said speech model server receiving the intermediate representation of the speech training data and generating a speech reference model using the intermediate representation, said speech model server further being operative to communicate the speech reference model to said first computing device; and a lexicon coupled to said speech recognizer for storing the speech reference model on said first computing device.
Claim 3
Dependent Claim
39 words
The speech processing system of claim 1 wherein said speech recognizer receives alphanumeric text that serves as the speech training data and said intermediate representation of the speech training data being a sequence of symbols from said alphanumeric text.
Claim 4
Dependent Claim
35 words
The speech processing system of claim 1 wherein said speech recognizer captures audio data that serves as the speech training data and digitizes the audio data into said intermediate representation of the speech training data.
Claim 5
Dependent Claim
57 words
The speech processing system of claim 1 wherein said speech recognizer captures audio data that serves as the speech training data and converts the audio data into a vector of parameters that serves as said intermediate representation of the speech data, where the parameters are indicative of the short term speech spectral shape of said audio data.
Claim 6
Dependent Claim
33 words
The speech processing system of claim 4 wherein said vector of parameters is further defined as either pulse code modulation (PCM), μ-law encoded PCM, filter bank energies, line spectral frequencies, or cepstral coefficients.
Claim 7
Dependent Claim
57 words
The speech processing system of claim 1 wherein said speech model server further comprises a speech model database for storing speaker-independent speech reference models, said speech model server being operative to retrieve a speech reference model from said speech model database that corresponds to the intermediate representation of said speech training data received from said speech recognizer.
Claim 8
Dependent Claim
49 words
The speech processing system of claim 1 wherein said speech model server further comprises: a phoneticizer receptive of the intermediate representation for producing a plurality of phonetic transcriptions; and a model trainer coupled to said phoneticizer for building said speech reference model based on said plurality of phonetic transcriptions.
Claim 9
Dependent Claim
65 words
The speech processing system of claim 4 wherein said speech model server further comprises: a Hidden Markov Model (HMM) database for storing phone model speech data corresponding to a plurality of phonemes; and a model trainer coupled to said HMM database for decoding the vector of parameters into a phonetic transcription of the audio data, whereby said phonetic transcription serves as said speech reference model.
Claim 10
Dependent Claim
74 words
The speech processing system of claim 1 wherein said speech recognizer captures at least two training repetitions of audio data that serves as the speech training data and converts the audio data into a sequence of vectors of parameters that serves as said intermediate representation of the speech training data, where each vector corresponds to a training repetition and the parameters are indicative of the short term speech spectral shape of said audio data.
Claim 11
Dependent Claim
68 words
The speech processing system of claim 9 wherein said speech model server being operative to determine a reference vector from the sequence of vectors, align each vector in the sequence of vectors to the reference vector, determine a mean and a variance of each parameter in the reference vector computed over the values in the aligned vectors, thereby constructing said speech reference model from the sequence of vectors.
Claim 12
Dependent Claim
157 words
A distributed speech processing system for supporting applications that reside on a personal digital assistant (PDA) device, comprising: an input means for capturing speech training data at the PDA; a speech recognizer coupled to said input means and receptive of speech training data from said input means; said speech recognizer being operative to process the speech training data into an intermediate representation of the speech training data and communicate the intermediate representation to a second computing device; a speech model server residing on said second computing device, said second computing device being interconnected via a network to the PDA; said speech model server receiving the intermediate representation of the speech training data and generating a speech reference model using the intermediate representation, said speech model server further being operative to communicate the speech reference model to said first computing device; and a lexicon coupled to said speech recognizer for storing the speech reference model on the PDA.
Claim 13
Dependent Claim
157 words
A distributed speech processing system for supporting applications that reside on a personal digital assistant (PDA) device, comprising: an input means for capturing speech training data at the PDA; a speech recognizer coupled to said input means and receptive of speech training data from said input means; said speech recognizer being operative to process the speech training data into an intermediate representation of the speech training data and communicate the intermediate representation to a second computing device; a speech model server residing on said second computing device, said second computing device being interconnected via a network to the PDA; said speech model server receiving the intermediate representation of the speech training data and generating a speech reference model using the intermediate representation, said speech model server further being operative to communicate the speech reference model to said first computing device; and a lexicon coupled to said speech recognizer for storing the speech reference model on the PDA.
Claim 14
Dependent Claim
51 words
The distributed speech processing system of claim 11 wherein said input means is further defined as: a stylus; a display pad for capturing handwritten stroke data from the stylus; and a handwritten recognition module for converting handwritten stroke data into alphanumeric data, whereby the alphanumeric data serves as speech training data.
Claim 15
Dependent Claim
32 words
The distributed speech processing system of claim 12 wherein said speech recognizer segments the alphanumeric data into a sequence of symbols which serves as the intermediate representation of the speech training data.
Claim 16
Dependent Claim
58 words
The distributed speech processing system of claim 11 wherein said speech model server further comprises a speech model database for storing speaker-independent speech reference models, said speech model server being operative to retrieve a speech reference model from said speech model database that corresponds to the intermediate representation of said speech training data received from said speech recognizer.
Claim 17
Dependent Claim
50 words
The distributed speech processing system of claim 11 wherein said speech model server further comprises: a phoneticizer receptive of the intermediate representation for producing a plurality of phonetic transcriptions; and a model trainer coupled to said phoneticizer for building said speech reference model based on said plurality of phonetic transcriptions.
Claim 18
Dependent Claim
28 words
The distributed speech processing system of claim 11 wherein said input means is further defined as a microphone for capturing audio data that serves as speech training data.
Claim 19
Dependent Claim
58 words
The distributed speech processing system of claim 16 wherein said speech recognizer converts the audio data into a digital input signal and translates the digital input signal into a vector of parameters which serves as the intermediate representation of the speech training data, said parameters being indicative of the short term speech spectral shape of said audio data.
Claim 20
Dependent Claim
34 words
The distributed speech processing system of claim 17 wherein said vector of parameters is further defined as either pulse code modulation (PCM), μ-law encoded PCM, filter bank energies, line spectral frequencies, or cepstral coefficients.
Claim 21
Dependent Claim
66 words
The distributed speech processing system of claim 11 wherein said speech model server further comprises: a Hidden Markov Model (HMM) database for storing phone model speech data corresponding to a plurality of phonemes; and a model trainer coupled to said HMM database for decoding said vector of parameters into a phonetic transcription of the audio data, whereby said phonetic transcription serves as said speech reference model.
Claim 22
Dependent Claim
74 words
The speech processing system of claim 11 wherein said speech recognizer captures at least two training repetitions of audio data that serves as the speech training data and converts the audio data into a sequence of vectors of parameters that serves as said intermediate representation of the speech training data, where each vector corresponds to a training repetition and the parameters are indicative of the short term speech spectral shape of said audio data.
Claim 23
Dependent Claim
68 words
The speech processing system of claim 20 wherein said speech model server being operative to determine a reference vector from the sequence of vectors, align each vector in the sequence of vectors to the reference vector, determine a mean and a variance of each parameter in the reference vector computed over the values in the aligned vectors, thereby constructing said speech reference model from the sequence of vectors.
Claim 24
Dependent Claim
159 words
A distributed speech processing system for supporting applications that reside on a cellular telephone handset device, comprising: an input means for capturing speech training data at the handset device; a speech recognizer coupled to said input means and receptive of speech training data from said input means; said speech recognizer being operative to process the speech training data into an intermediate representation of the speech training data and communicate the intermediate representation to a second computing device; a speech model server residing on said second computing device, said second computing device being interconnected via a network to the handset device; said speech model server receiving the intermediate representation of the speech training data and generating a speech reference model using the intermediate representation, said speech model server further being operative to communicate the speech reference model to said first computing device; and a lexicon coupled to said speech recognizer for storing the speech reference model on the handset device.
Claim 25
Dependent Claim
159 words
A distributed speech processing system for supporting applications that reside on a cellular telephone handset device, comprising: an input means for capturing speech training data at the handset device; a speech recognizer coupled to said input means and receptive of speech training data from said input means; said speech recognizer being operative to process the speech training data into an intermediate representation of the speech training data and communicate the intermediate representation to a second computing device; a speech model server residing on said second computing device, said second computing device being interconnected via a network to the handset device; said speech model server receiving the intermediate representation of the speech training data and generating a speech reference model using the intermediate representation, said speech model server further being operative to communicate the speech reference model to said first computing device; and a lexicon coupled to said speech recognizer for storing the speech reference model on the handset device.
Claim 26
Dependent Claim
53 words
The distributed speech processing system of claim 22 wherein said input means is further defined as a keypad for capturing alphanumeric data that serves as speech training data, such that said speech recognizer segments the alphanumeric data into a sequence of symbols which serves as the intermediate representation of the speech training data.
Claim 27
Dependent Claim
58 words
The distributed speech processing system of claim 22 wherein said reference model server further comprises a speech model database for storing speaker-independent speech reference models, said reference model server being operative to retrieve a speech reference model from said speech model database that corresponds to the intermediate representation of said speech training data received from said speech recognizer.
Claim 28
Dependent Claim
50 words
The distributed speech processing system of claim 22 wherein said speech model server further comprises: a phoneticizer receptive of the intermediate representation for producing a plurality of phonetic transcriptions; and a model trainer coupled to said phoneticizer for building said speech reference model based on said plurality of phonetic transcriptions.
Claim 29
Dependent Claim
28 words
The distributed speech processing system of claim 22 wherein said input means is further defined as a microphone for capturing audio data that serves as speech training data.
Claim 30
Dependent Claim
58 words
The distributed speech processing system of claim 26 wherein said speech recognizer converts the audio data into a digital input signal and translates the digital input signal into a vector of parameters which serves as the intermediate representation of the speech training data, said parameters being indicative of the short term speech spectral shape of said audio data.
Claim 31
Dependent Claim
34 words
The distributed speech processing system of claim 27 wherein said vector of parameters is further defined as either pulse code modulation (PCM), μ-law encoded PCM, filter bank energies, line spectral frequencies, or cepstral coefficients.
Claim 32
Dependent Claim
66 words
The distributed speech processing system of claim 22 wherein said speech model server further comprises: a Hidden Markov Model (HMM) database for storing phone model speech data corresponding to a plurality of phonemes; and a model trainer coupled to said HMM database for decoding said vector of parameters into a phonetic transcription of the audio data, whereby said phonetic transcription serves as said speech reference model.
Claim 33
Dependent Claim
75 words
The distributed speech processing system of claim 22 wherein said speech recognizer captures at least two training repetitions of audio data that serves as the speech training data and converts the audio data into a sequence of vectors of parameters that serves as said intermediate representation of the speech training data, where each vector corresponds to a training repetition and the parameters are indicative of the short term speech spectral shape of said audio data.
Claim 34
Dependent Claim
70 words
The distributed speech processing system of claim 30 wherein said speech model server being operative operative to determine a reference vector from the sequence of vectors, align each vector in the sequence of vectors to the reference vector, determine a mean and a variance of each parameter in the reference vector computed over the values in the aligned vectors, thereby constructing said speech reference model from the sequence of vectors.
Claim 35
Independent Claim
105 words
A method of building speech reference models for use in a speech recognition system, comprising the steps of: collecting speech training data at a first computing device; processing the speech training data into an intermediate representation of the speech training data on said first computing device; communicating said intermediate representation of the speech training data to a second computing device, said second computing device interconnected via a network to said first computing device; creating a speech reference model from said intermediate representation at said second computing device; and communicating said speech reference model to the first computing device for use in the speech recognition system.
Claim 36
Independent Claim
105 words
A method of building speech reference models for use in a speech recognition system, comprising the steps of: collecting speech training data at a first computing device; processing the speech training data into an intermediate representation of the speech training data on said first computing device; communicating said intermediate representation of the speech training data to a second computing device, said second computing device interconnected via a network to said first computing device; creating a speech reference model from said intermediate representation at said second computing device; and communicating said speech reference model to the first computing device for use in the speech recognition system.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2005-10-07 | 2006-04-08 | 2006-10-08 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2009-10-07 | 2010-04-08 | 2010-10-08 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2013-10-07 | 2014-04-08 | 2014-10-08 | $7700.00 | Window Closed / Lapsed |