Statistical Parametric Speech Synthesis Based on the Degree of Articulation (2013)
Abstract / truncated to 115 words
Nowadays, speech synthesis is part of various daily life applications. The ultimate goal of such technologies consists in extending the possibilities of interaction with the machine, in order to get closer to human-like communications. However, current state-of-the-art systems often lack of realism: although high-quality speech synthesis can be produced by many researchers and companies around the world, synthetic voices are generally perceived as hyperarticulated. In any case, their degree of articulation is fixed once and for all. The present thesis falls within the more general quest for enriching expressivity in speech synthesis. The main idea consists in improving statistical parametric speech synthesis, whose most famous example is Hidden Markov Model (HMM) based speech synthesis, by ...
hmm-based speech synthesis – speech analysis – expressive speech – degree of articulation – speaking style adaptation – speaking style transposition – voice quality – speech intelligibility
Information
- Author
- Picart, Benjamin
- Institution
- Université de Mons (UMONS)
- Supervisors
- Publication Year
- 2013
- Upload Date
- March 7, 2014
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