Statistical methods for speech recognition

@inproceedings{Jelinek1997StatisticalMF,
  title={Statistical methods for speech recognition},
  author={F. Jelinek},
  year={1997}
}
  • F. Jelinek
  • Published 1997
  • Computer Science, Mathematics
The speech recognition problem hidden Markov models the acoustic model basic language modelling the Viterbi search hypothesis search on a tree and the fast match elements of information theory the complexity of tasks - the quality of language models the expectation - maximization algorithm and its consequences decision trees and tree language models phonetics from orthography - spelling-to-base from mappings triphones and allophones maximum entropy probability estimation and language models… Expand
Network training for continuous speech recognition
Hierarchical Bayesian Language Models for Conversational Speech Recognition
Discriminative Models for Speech Recognition
  • M. Gales
  • Computer Science
  • 2007 Information Theory and Applications Workshop
  • 2007
Gaussian Mixture Language Models for Speech Recognition
  • M. Afify, O. Siohan, R. Sarikaya
  • Computer Science
  • 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07
  • 2007
An Empirical Exploration of Hidden Markov Models: From Spelling Recognition to Speech Recognition
1 LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION
Prosodic features for a maximum entropy language model
Spontaneous speech recognition using HMMs
Hidden Model Sequence Models for Automatic Speech Recognition
...
1
2
3
4
5
...

References

SHOWING 1-4 OF 4 REFERENCES
Fundamentals of speech recognition
Statistical Learning by 8-Month-Old Infants
With Greg Adams, he has written several papers on HMM-based approaches to part-of-speech tagging of text. Neufeld's address is