You et al., 2010 - Google Patents
A GMM-supervector approach to language recognition with adaptive relevance factorYou et al., 2010
View PDF- Document ID
- 6642923959716334346
- Author
- You C
- Li H
- Lee K
- Publication year
- Publication venue
- 2010 18th European Signal Processing Conference
External Links
Snippet
Gaussian mixture model (GMM) supervector has been proven effective for language recognition. While a speech utterance can be represented with a GMM which can be obtained through maximum a posteriori (MAP) criterion, it is observed that the supervector …
- 230000003044 adaptive 0 title abstract description 11
Classifications
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- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
- G10L15/065—Adaptation
- G10L15/07—Adaptation to the speaker
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
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- G10L15/18—Speech classification or search using natural language modelling
- G10L15/183—Speech classification or search using natural language modelling using context dependencies, e.g. language models
- G10L15/187—Phonemic context, e.g. pronunciation rules, phonotactical constraints or phoneme n-grams
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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