Neural Networks or Hidden Markov Models for Automatic Speech Recognition: Is there a Choice?
- 1 January 1992
- book chapter
- Published by Springer Nature
Abstract
No abstract availableKeywords
This publication has 12 references indexed in Scilit:
- Connectionist Viterbi training: a new hybrid method for continuous speech recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Speaker-independent word recognition using a neural prediction modelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Combining hidden Markov model and neural network classifiersPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Large vocabulary recognition using linked predictive neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Continuous speech recognition using multilayer perceptrons with hidden Markov modelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Word recognition using hidden control neural architecturePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Speech pattern discrimination and multilayer perceptronsComputer Speech & Language, 1989
- Speech recognition with continuous-parameter hidden Markov modelsComputer Speech & Language, 1987
- The Acoustic-Modeling Problem in Automatic Speech Recognition.Published by Defense Technical Information Center (DTIC) ,1987
- A Learning Algorithm for Boltzmann Machines*Cognitive Science, 1985