Abstract:
The HMM as a suitable model for time sequence modeling is used for estimation of speech synthesis parameters, A speech parameter sequence is generated from HMMs themselves whose observation vectors consists of spectral parameter vector and its dynamic feature vectors. HMMs generate cepstral coefficients and pitch parameter which are then fed to speech synthesis filter named Mel Log Spectral Approximation (MLSA), this paper explains how this approach can be applied to the Arabic language to produce intelligent Arabic speech synthesis using the HMM- Based Speech Synthesis and the influence of using of the dynamic features and the increasing of the number of mixture components on the quality enhancement of the Arabic speech synthesized.
