Keshet et al., 2011 - Google Patents
Pac-bayesian approach for minimization of phoneme error rateKeshet et al., 2011
View PDF- Document ID
- 12663854282134649702
- Author
- Keshet J
- McAllester D
- Hazan T
- Publication year
- Publication venue
- 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
External Links
Snippet
We describe a new approach for phoneme recognition which aims at minimizing the phoneme error rate. Building on structured prediction techniques, we formulate the phoneme recognizer as a linear combination of feature functions. We state a PAC-Bayesian …
- 238000000034 method 0 abstract description 3
Classifications
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- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L15/14—Speech classification or search using statistical models, e.g. hidden Markov models [HMMs]
- G10L15/142—Hidden Markov Models [HMMs]
- G10L15/144—Training of HMMs
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- G—PHYSICS
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- G10L15/065—Adaptation
- G10L15/07—Adaptation to the speaker
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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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- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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