Title
Postfilters to Modify the Modulation Spectrum for Statistical Parametric Speech Synthesis.
Abstract
This paper presents novel approaches based on modulation spectrum (MS) for high-quality statistical parametric speech synthesis, including text-to-speech (TTS) and voice conversion (VC). Although statistical parametric speech synthesis offers various advantages over concatenative speech synthesis, the synthetic speech quality is still not as good as that of concatenative speech synthesis or the qu...
Year
DOI
Venue
2016
10.1109/TASLP.2016.2522655
IEEE/ACM Transactions on Audio, Speech, and Language Processing
Keywords
Field
DocType
Speech,Hidden Markov models,Natural languages,Speech synthesis,Modulation,Yttrium,Probability density function
Speech synthesis,Pattern recognition,Regression,Computer science,Utterance,Speech recognition,Parametric statistics,Natural language,Artificial intelligence,Hidden Markov model,Probability density function,Mixture model
Journal
Volume
Issue
ISSN
24
4
2329-9290
Citations 
PageRank 
References 
12
0.93
43
Authors
6
Name
Order
Citations
PageRank
Shinnosuke Takamichi17522.08
Tomoki Toda21874167.18
Alan W. Black34391742.28
Graham Neubig4989130.31
Sakriani Sakti525765.02
Satoshi Nakamura61099194.59