Multi-space distribution for pattern recognition based on mixed continuous and discrete observations
First Claim
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1. A method of performing speech recognition on a tonal language, comprising:
- obtaining a datastore on a tangible medium including a plurality of tonal models each having a multi-space distribution, wherein each tonal model corresponds to a known syllable in a language;
receiving a first data stream indicative of an observation of an utterance having a discrete tonal feature and a continuous tonal feature and a second data stream indicative of spectral features of a syllable of the utterance; and
outputting a recognition result by;
comparing the first data stream against at least one of the plurality of tonal models; and
comparing a portion of the second data stream against a spectral model.
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Abstract
Performing speech recognition on a tonal language is done using a plurality of tonal models. Each tonal model has a multi-space distribution and corresponds to a known syllable in a language. A first data stream indicative of an observation of an utterance is received. The observation has both a discrete and a continuous tonal feature. A second data stream indicative of spectral features of a syllable of an utterance is also received. The first data stream is compared against at least one of the plurality of tonal models and the second data stream is compared against a spectral model.
27 Citations
20 Claims
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1. A method of performing speech recognition on a tonal language, comprising:
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obtaining a datastore on a tangible medium including a plurality of tonal models each having a multi-space distribution, wherein each tonal model corresponds to a known syllable in a language; receiving a first data stream indicative of an observation of an utterance having a discrete tonal feature and a continuous tonal feature and a second data stream indicative of spectral features of a syllable of the utterance; and outputting a recognition result by; comparing the first data stream against at least one of the plurality of tonal models; and comparing a portion of the second data stream against a spectral model. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method of generating a tonal model for modeling tonal features of an utterance, comprising:
creating a plurality of tonal models each having a multi-space distribution, wherein each tonal model corresponds to a known syllable in a language, the plurality of tonal models being configured such that they can be compared against tonal features in an utterance to be recognized. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15)
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16. A system for recognizing an observed pattern having both a continuous and discrete component, comprising:
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a database including a plurality of models each having a multi-space distribution, wherein each model corresponds to a known pattern that can be recognized; an interface configured to receive a signal indicative of an observed pattern; and an analyzer configured to compare the signal against one or more of the plurality of models. - View Dependent Claims (17, 18, 19, 20)
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Specification