HMM Based Text-to-Speech Synthesis for Telugu

Gugulothu, Narendhar (2016) HMM Based Text-to-Speech Synthesis for Telugu. Masters thesis, Indian Institute of Technology Hyderabad.

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This thesis describes a novel approach to build a general purpose working Telugu text-to- speech synthesis system (TTS) based on hidden Markov model (HMM) which is reasonably intelligible, natural sounding and exible. There have been several attempts proposed to use HMM for constructing TTS systems. Most of such systems are based on waveform concatenation techniques. To fully convey information present in speech signals, text-to-speech synthesis systems are required to have an ability to generate natural sounding speech with arbitrary speakers individualities and emotions (e.g., anger, sadness, joy). To represent all these factors the Mel- cepstral coefficients are extracted as spectral parameters. Excitation parameters are extracted using fundamental frequency(F0).

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IITH Creators:
IITH CreatorsORCiD
Item Type: Thesis (Masters)
Uncontrolled Keywords: hidden Markov model, dynamic parameters
Subjects: Physics > Electricity and electronics
Divisions: Department of Electrical Engineering
Depositing User: Library Staff
Date Deposited: 24 Jun 2016 05:36
Last Modified: 30 Jul 2019 06:00
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