Simple methods for improving speaker-similarity of HMM-based speech synthesis

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2010, Pages 4610-4613

  Yamagishi, Junichi ^a   King, Simon ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

HMM; HTS; Speech synthesis; TTS

Indexed keywords

SIGNAL PROCESSING; SPEECH RECOGNITION;

'CURRENT; FREQUENCY WARPING; HMM; HMM-BASED SPEECH SYNTHESIS; HTS; LOGARITHMIC SCALING; SAMPLING RATES; SIMPLE METHOD; TTS; WAVEFORMS;

SPEECH SYNTHESIS;

EID: 78049403515     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2010.5495562     Document Type: Conference Paper

References (18)

1. H. Zen, K. Tokuda, and A. W. Black, "Statistical parametric speech synthesis," Speech Communication, vol. 51, no. 11, pp. 1039-1064, Nov. 2009.
2. V. Karaiskos, S. King, R. A. J. Clark, and C. Mayo, "The Blizzard Challenge 2008," in Proc. Blizzard Challenge Workshop, Brisbane, Australia, Sep. 2008.
3. J. Yamagishi, H. Zen, Y.-J. Wu, T. Toda, and K. Tokuda, "The HTS-2008 system: Yet another evaluation of the speaker-adaptive HMM-based speech synthesis system in the 2008 Blizzard Challenge," in Proc. Blizzard Challenge 2008, Brisbane, Australia, Sep. 2008.
4. E. Zwicker and B. Scharf, "A model of loudness summation," Psych. Rev., vol. 72, pp. 2-26, 1965.
5. T. Yoshimura, K. Tokuda, T. Masuko, T. Kobayashi, and T. Kitamura, "Incorporation of mixed excitation model and postfilter into HMM-based text-to-speech synthesis," IEICE Trans., vol. J87-D-II, no. 8, pp. 1565-1571, Aug. 2004, (in Japanese).
6. H. Fujisaki and K. Hirose, "Analysis of voice fundamental frequency contours for declarative sentences of Japanese," J. Acoust. Soc. Japan (E), vol. 5, no. 4, pp. 233-242, Oct. 2000.
7. J. Yamagishi et al., "Thousands of voices for HMM-based speech synthesis," in Proc. Interspeech 2009, Brighton, U.K., Sep. 2009, pp. 420-423.
8. G. E. P. Box and D. R. Cox, "An analysis of transformations," Journal of the Royal Statistical Society. Series B (Methodological), vol. 26, no. 2, pp. 211-252, 1964.
9. K. Tokuda, T. Kobayashi, T. Fukada, H. Saito, and S. Imai, "Spectral estimation of speech based on mel-cepstral representation," IEICE Trans. Fundamentals, vol. J74-A, no. 8, pp. 1240-1248, Aug. 1991, in Japanese.
10. K. Tokuda, T. Kobayashi, and S. Imai, "Recursive calculation of mel-cepstrum from LP coefficients," in Technical Report of Nagoya Institute of Technology, Apr. 1994.
11. R. Patterson, "Auditory filter shapes derived with noise stimuli," Journal of the Acoustical Society of America, vol. 76, pp. 640-654, Mar. 1982.
12. J. O. Smith III and J. S. Abel, "Bark and ERB bilinear transforms," IEEE Trans. on Speech Audio Process., vol. 7, no. 6, pp. 697-708, Jul. 1999.
13. S. S. Chen and R. A. Gopinath, "Gaussianization," in NIPS 2000, Nov. 2000, pp. 423-429.
14. S. Fitt and S. Isard, "Synthesis of regional English using a keyword lexicon," in Proc. Eurospeech 1999, vol. 2, Sep. 1999, pp. 823-826.
15. R. A. J. Clark, K. Richmond, and S. King, "Multisyn: Open-domain unit selection for the Festival speech synthesis system," Speech Communication, vol. 49, no. 4, pp. 317-330, 2007.
16. H. Zen, T. Toda, M. Nakamura, and K. Tokuda, "Details of Nitech HMM-based speech synthesis system for the Blizzard Challenge 2005," IEICE Trans. Inf. & Syst., vol. E90-D, no. 1, pp. 325-333, Jan. 2007.
17. H. Kawahara, I. Masuda-Katsuse, and A. Cheveigné, "Restructuring speech representations using a pitch-adaptive time-frequency smoothing and an instantaneous-frequency-based F0 extraction: possible role of a repetitive structure in sounds," Speech Communication, vol. 27, pp. 187-207, 1999.
18. Y. Wu and R.-H. Wang, "Minimum generation error training for HMM-based speech synthesis," in Proc. ICASSP 2006, May 2006, pp. 89-92.