Text-to-Speech Synthesis for Hindi Language Using MFCC and LPC Feature Extraction Techniques

Shaikh Naziya Sultana; Ratnadeep R. Deshmukh

doi:10.46947/joaasr632024943

Authors

Shaikh Naziya Sultana Department of Computer Science and IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MH), INDIA.
Ratnadeep R. Deshmukh Department of Computer Science and IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MH), INDIA.

DOI:

https://doi.org/10.46947/joaasr632024943

Keywords:

Devanagari; Text-to-Speech (TTS); Hindi language; DCT; MFCC; LPC

Abstract

India is a large country with over a billion populations who speak numerous languages. 43% of Indians speak Devanagari Hindi script, followed by Bengali, Telugu, Marathi, and other languages. The widespread generation of content and accessibility would therefore greatly benefit from text-to-speech systems for such languages. In this research work we improve the already available Text-to-Speech (TTS) system using advance preprocessing techniques to the Hindi corpus database and applied various feature extraction techniques for better result. Finally we got the accuracy as 98% using MFCC and LPC feature extraction techniques. The developed model is capable for getting the input from audio file and read it loudly using developed TTS system.

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