Prosody Correction Preserving Speaker Individuality for Chinese-Accented Japanese HMM-Based Text-to-Speech Synthesis
Author:
Affiliation:
1. University of Tokyo
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://www.jstage.jst.go.jp/article/transinf/E102.D/6/E102.D_2018EDL8264/_pdf
Reference15 articles.
1. [1] K. Tokuda, Y. Nankaku, T. Toda, H. Zen, J. Yamagishi, and K. Oura, “Speech synthesis based on hidden Markov models,” Proceedings of the IEEE, vol.101, no.5, pp.1234-1252, 2013. 10.1109/jproc.2013.2251852
2. [2] H. Ze, A. Senior, and M. Schuster, “Statistical parametric speech synthesis using deep neural networks,” in Proc. ICASSP, May 2013. 10.1109/icassp.2013.6639215
3. [3] Y. Wang, R. Skerry-Ryan, D. Stanton, Y. Wu, R.J. Weiss, N. Jaitly, Z. Yang, Y. Xiao, Z. Chen, S. Bengio, Q. Le, Y. Agiomyrgiannakis, R. Clark, and R.A. Saurous, “Tacotron: Towards end-to-end speech synthesis,” Interspeech 2017, pp.4006-4010, 2017. 10.21437/interspeech.2017-1452
4. [4] Y. Oshima, S. Takamichi, T. Toda, G. Neubig, S. Sakti, and S. Nakamura, “Non-native text-to-speech preserving speaker individuality based on partial correction of prosodic and phonetic characteristics,” IEICE Trans. Inf. & Syst., vol.E99-D, no.12, pp.3132-3139, 2016. 10.1587/transinf.2016edp7231
5. [5] J. Yamagishi, T. Kobayashi, Y. Nakano, K. Ogata, and J. Isogai, “Analysis of speaker adaptation algorithms for HMM-based speech synthesis and a constrained SMAPLR adaptation algorithm,” IEEE Trans. Audio, Speech, Language Process., vol.17, no.1, pp.66-83, 2009. 10.1109/tasl.2008.2006647
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