Statistical methods for speech recognition

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 three applications of maximum entropy estimation to language modelling estimation of probabilities from counts and the Back-Off method.

[1]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[2]  R N Aslin,et al.  Statistical Learning by 8-Month-Old Infants , 1996, Science.

[3]  Geoffrey Zweig,et al.  Speech Recognition with Dynamic Bayesian Networks , 1998, AAAI/IAAI.