HMM Based Kannada Speech Synthesis using Festvox

Abstract

The process which involves generation of human like voice by a machine is called speech synthe- sis. The developments in the fteld of speech synthesis is vast in international languages, but it is limited in Indian languages like Kannada. This work aims at de- velopment of such a system for Kannada language using Festival and Festvox. It is based on parametric analysis and models of speech features, particular to a language and speaker. The system is memoryless and dynamic, wherein only extracted features are stored but not recorded audio. The training process involves speech data acquisition, pre-processing, labelling using Baum- Welch Iteration, whereas testing process involves text analysis, text segmentation, speech synthesis and qual- ity enhancement using acoustic HMM model develop- ment. The quality of synthesis is 3.52 dB to 5.02 dB as measured by Mel-Cepstral Distortion (MCD) score.