Le Modele De Markov Cache Mmc A Deux Niveaux Application A La Modelisation De La Duree Dans Un Dispositif De Reconnaissance De Parole A Two Level Hmm Application To The Sound Duration Modelling In A Speech Recognition System

Le modèle de Markov caché (MMC) à deux niveaux: application à la modélisation de la durée dans un dispositif de reconnaissance de parole [A two-level HMM: application to the sound duration modelling in a speech recognition system]

Le modèle de Markov caché (MMC) à deux niveaux

Markov Models for Pattern Recognition

This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.