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the HMM-Based Speech Synthesis and ..

Speech Synthesis and Its Applications

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Reactive and continuous control of HMM-based speech synthesis

The focus is to learn the behavior of Urdu intonation and its relation with Urdu syntax to develop an Urdu language based text-to speech synthesis system.

29/08/2014 · This paper describes a technique for language ..

This research paper describes the Impalement of the first, usable, Marathi Text to Speech system for Maharashtra Marathi using the open source Festival TTS engine. Besides that, this research paper also discusses a few practical applications that use this system. This system is developed using di-phone concatenation approach in its waveform generation phase. Construction of a di-phone database and implementation of the natural language processing modules are described. Natural language processing modules include text processing, tokenizing and grapheme to phoneme (G2P) conversion that were written in Festival's format. Finally, a test was conducted to evaluate the intelligibility of the synthesized speech.

Its Applications to Speech Synthesis, Speech ..

24/09/2016 · Reactive and continuous control of HMM-based speech synthesis. Maria Astrinaki, Nicolas D'Alessandro, Benjamin Picart, Thomas Drugman, Thierry Dutoit

Brennan, "Comparative performance of spectral subtraction and HMM-based speech enhancement strategies with application to hearing and design," in , Adelaide, Australia, 1994, pp.

This thesis describes a novel approach to text-to-speech synthesis (TTS) based on hidden Markov model (HMM). There have been several attempts proposed to utilize HMM for constructing TTS systems. Most of such systems are based on waveform concatenation techniques. In the proposed approach, on the contrary, speech parameter sequences are generated from HMM directly based on maximum likelihood criterion. By considering relationship between static and dynamic parameters, smooth spectral sequences are generated according to the statistics of static and dynamic parameters modeled by HMMs. As a result, natural sounding speech can be synthesized. Subjective experimental results demonstrate the effectiveness of the use of dynamic features. Relationship between model complexity and synthesized speech quality is also investigated. To synthesize speech, fundamental frequency (F0) patterns are also required to be modeled and generated. The conventional discrete or continuous HMMs, however, cannot be applied for modeling F0 patterns, since observation

Energy, & Industry Applications; ..

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  • 26/07/2014 · Language and Technology Conference

    15/03/2010 · ..

  • Authors; Authors and affiliations;

    09/04/2017 · Usage of the HMM-Based Speech Synthesis for Intelligent Arabic Voice

  • The first computer-based speech-synthesis ..

    Improved Syllable-Based Text to Speech Synthesis for Tone Language Systems

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