Extracting MFCC, F0 feature in Vietnamese HMMbased speech synthesis

HMM-based statistical speech synthesis method is not requiring a very large speech corpus for training the system. In this system, statistical modeling is applied to learn distributions of context-dependent acoustic vectors extracted from speech signals, each vector containing a suitable parametric representation of one speech frame and Vietnamese phonetic rules to synthesize speech. The method presented in this paper allows accurate MFCC, F0 and tone extraction and high-quality reconstruction of speech signals. Its suitability for high-quality HMM-based speech synthesis is shown through evaluations subjectively.