• Citer

Viterbi algorithm for acoustic vectors generated by a linear stochastic differential equation on each state

par Saerens, Marco
Référence ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 1, page (233-236)
Publication Publié, 1995

Article révisé par les pairs

• Détails
• Contenu

Résumé :

When using the hidden Markov models for speech recognition, it is usually assumed that the probability for a particular acoustic vector is emitted at a given time only depends on the current state and the current acoustic vector observed. This paper introduces another idea, i.e., in a given state, the acoustic vectors are generated by a linear stochastic differential equation. This extends a previous study in which it was assumed that the acoustic vectors are generated by a continuous Markov process. This is motivated by the fact that the time evolution of the acoustic vector is inherently dynamic and continuous, so that modeling could be performed in the continuous-time domain instead of the discrete-time domain.