A probabilistic framework for feature-based speech recognition
- 24 December 2002
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 4, 2277-2280
- https://doi.org/10.1109/icslp.1996.607261
Abstract
No abstract availableKeywords
This publication has 20 references indexed in Scilit:
- SAPPHIRE: an extensible speech analysis and recognition tool based on Tcl/TkPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- State clustering in hidden Markov model-based continuous speech recognitionComputer Speech & Language, 1994
- Phonetic transition modeling for continuous speech recognitionThe Journal of the Acoustical Society of America, 1994
- High accuracy phone recognition using context clustering and quasi-triphonic modelsComputer Speech & Language, 1994
- ML estimation of a stochastic linear system with the EM algorithm and its application to speech recognitionIEEE Transactions on Speech and Audio Processing, 1993
- Recent progress on the SUMMIT systemPublished by Association for Computational Linguistics (ACL) ,1990
- Automatic recognition of keywords in unconstrained speech using hidden Markov modelsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
- Speaker-independent phone recognition using hidden Markov modelsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1989
- A stochastic segment model for phoneme-based continuous speech recognitionIEEE Transactions on Acoustics, Speech, and Signal Processing, 1989
- Segmenting speech using dynamic programmingThe Journal of the Acoustical Society of America, 1981