IMPLEMENTING AN HSMM-BASED SPEECH SYNTHESIS SYSTEM USING AN EFFICIENT FORWARD-BACKWARD ALGORITHM
Heiga Zen · 2007
A statistical parametric speech synthesis system based on hidden semi-Markov models (HSMMs) has been developed. In the training and synthesis part of the system, the expectation-maximization (EM) algorithm is used. To perform the expectation step of the EM algorithm, this system has used a forward-backward algorithm which was proposed by Ferguson and refined by Levinson. Recently, Yu and Kobayashi proposed a more efficient forward-backward algorithm. In this report, we re-derive parameter reestimation formulae and the speech parameter generation algorithm based on the new efficient forward-backward algorithm.