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 [BibTeX] [Marc21]
VTLN Adaptation for Statistical Speech Synthesis
Type of publication: Conference paper
Citation: Saheer_ICASSP_2010
Booktitle: Proceedings of ICASSP
Year: 2010
Location: Dallas, Texas
Abstract: The advent of statistical speech synthesis has enabled the unification of the basic techniques used in speech synthesis and recognition. Adaptation techniques that have been successfully used in recognition systems can now be applied to synthesis systems to improve the quality of the synthesized speech. The application of vocal tract length normalization (VTLN) for synthesis is explored in this paper. VTLN based adaptation requires estimation of a single warping factor, which can be accurately estimated from very little adaptation data and gives additive improvements over CMLLR adaptation. The challenge of estimating accurate warping factors using higher order features is solved by initializing warping factor estimation with the values calculated from lower order features.
Projects Idiap
Authors Saheer, Lakshmi
Garner, Philip N.
Dines, John
Liang, Hui
Crossref by Saheer_Idiap-RR-41-2009
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  • Saheer_ICASSP_2010.pdf
       (From the proceedings)