Specifics of hidden Markov model modifications for large vocabulary continuous speech recognition
Specifics of hidden Markov model-based speech recognition are investigated. Influence of modeling simple and context-dependent phones, using simple Gaussian, two and three-component Gaussian mixture probability density functions for modeling feature distribution, and incorporating language model are discussed. Word recognition rates and model complexity criteria are used for evaluating suitability of these modifications for practical applications. Development of large vocabulary continuous speech recognition system using HTK toolkit and WSJCAMO English speech corpus is described. Results of experimental investigations are presented.
hidden markov model large vocabulary continuous speech recognition context-dependent phones gaussian mixture language modeling htk viterbi recognition beam search wsjcam0