HMM based Kannada speech synthesis using festvox

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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.

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APA

Chakrasali, S. V., Indira, K., Sharma, S. B., Srinivas, N. M., & Varun, S. S. (2019). HMM based Kannada speech synthesis using festvox. International Journal of Recent Technology and Engineering, 8(3), 2635–2639. https://doi.org/10.35940/ijrte.C4934.098319

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