A stochastic segment model for phoneme-based continuous speech recognition
- 1 January 1989
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Acoustics, Speech, and Signal Processing
- Vol. 37 (12), 1857-1869
- https://doi.org/10.1109/29.45533
Abstract
No abstract availableThis publication has 15 references indexed in Scilit:
- A vector quantizer incorporating both LPC shape and energyPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Segment quantization for very-low-rate speech codingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- 1000-word speaker-independent continuous-speech recognition using hidden Markov modelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Large-vocabulary speaker-independent continuous speech recognition using HMMPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Network-based connected digit recognitionIEEE Transactions on Acoustics, Speech, and Signal Processing, 1987
- Frame-specific statistical features for speaker independent speech recognitionIEEE Transactions on Acoustics, Speech, and Signal Processing, 1986
- Recognition of phonemes using time-spectrum patternSpeech Communication, 1986
- Mixture autoregressive hidden Markov models for speech signalsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
- Isolated-word speech recognition using multisection vector quantization codebooksIEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
- Matrix quantizer design for LPC speech using the generalized Llyod algorithmIEEE Transactions on Acoustics, Speech, and Signal Processing, 1985