ACOUSTING MODEL ADAPTION SYSTEM

摘要

PURPOSE:To improve performance such as the speech recognition rate of a tutor-less speaker adaption system. CONSTITUTION:A probability model (all-phoneme Ergodic HMM) is generated by the ergodic combination of all phonemes learnt from the input speech of a standard speaker by a phoneme bigram probability value. Then, the mean value vector mu of an output probability distribution as a parameter of the probability model is learnt by a maximum likelihood estimating method of Baum- Welch by using an input speech whose vocalization contents are unknown and the mean value vector mu is corrected by a moving vector field smoothing system. Then, the learning and the correction of the mean value vector is repeated until the value of output likelihood to input speed data is converged.