On the use of machine learning in statistical parametric speech synthesis. Drugman, T; Moinet, M; and Dutoit, T. In Benelearn 2008. Spa, Belgium.
On the use of machine learning in statistical parametric speech synthesis [pdf]Paper  abstract   bibtex   
Statistical parametric speech synthesis has recently shown its ability to produce natu- ral sounding speech while keeping a certain flexibility for voice transformation without requiring a huge amount of data. This ab- stract presents how machine learning tech- niques such as Hidden Markov Models in gen- eration mode or context oriented clustering with decision trees are applied in speech syn- thesis. Fields that are investigated in our laboratory to improve this method are also discussed.
@inproceedings{drugman_use_2008,
	Author = {Drugman, T and Moinet, M and Dutoit, Thierry},
	Booktitle = {Benelearn 2008},
	Date = {2008},
	Date-Modified = {2016-09-22 20:24:15 +0000},
	File = {Attachment:files/3186/Drugman, Moinet, Dutoit - 2008 - On the use of machine learning in statistical parametric speech synthesis.pdf:application/pdf},
	Keywords = {speech synthesis, speech technology, statistical synthesis, text-to-speech},
	Publisher = {Spa, Belgium},
	Title = {On the use of machine learning in statistical parametric speech synthesis},
	Url = {http://tcts.fpms.ac.be/publications/papers/2008/benelearn_tdamtd.pdf},
	Abstract = {Statistical parametric speech synthesis has recently shown its ability to produce natu- ral sounding speech while keeping a certain flexibility for voice transformation without requiring a huge amount of data. This ab- stract presents how machine learning tech- niques such as Hidden Markov Models in gen- eration mode or context oriented clustering with decision trees are applied in speech syn- thesis. Fields that are investigated in our laboratory to improve this method are also discussed.},
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