Synthesizer voice quality of new languages calibrated with mean mel cepstral distortion

@inproceedings{Kominek2008SynthesizerVQ,
  title={Synthesizer voice quality of new languages calibrated with mean mel cepstral distortion},
  author={John Kominek and Tanja Schultz and Alan W. Black},
  booktitle={SLTU},
  year={2008}
}
When developing synthesizers for new languages one must select a phoneset, record phonetically balanced sentences, build up a pronunciation lexicon, and evaluate the results. An objective measure of voice quality can be very useful, provided it is calibrated across multiple speakers, languages, and databases. As a substitute for full listening tests, this paper adopts mean melcepstral distortion as a measure of spectral accuracy, and proposes systematic variation of a known English corpus as a… CONTINUE READING
Highly Cited
This paper has 93 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 37 extracted citations

Arabic text to speech synthesis based on neural networks for MFCC estimation

2013 World Congress on Computer and Information Technology (WCCIT) • 2013
View 5 Excerpts
Highly Influenced

Non-parallel Voice Conversion Using Generative Adversarial Networks

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) • 2018
View 9 Excerpts
Highly Influenced

Evaluating acoustic modelling of lexical stress for Afrikaans speech synthesis

2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech) • 2017
View 1 Excerpt

93 Citations

01020'10'13'16'19
Citations per Year
Semantic Scholar estimates that this publication has 93 citations based on the available data.

See our FAQ for additional information.