Segmental Pitch Control Using Speech Input Based on Differential Contexts and Features for Customizable Neural Speech Synthesis

Author:

Hanabusa Shinya,Nose Takashi,Ito Akinori

Publisher

Springer International Publishing

Reference8 articles.

1. Kawahara, H., Masuda-Katsuse, I., de Cheveigne, A.: 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 Commun. 27(3–4), 187–207 (1999)

2. Kingma, D., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)

3. Maeno, Y., Nose, T., Kobayashi, T., Koriyama, T., Ijima, Y., Nakajima, H., Mizuno, H., Yoshioka, O.: Prosodic variation enhancement using unsupervised context labeling for HMM-based expressive speech synthesis. Speech Commun. 57, 144–154 (2014)

4. Nishigaki, Y., Takamichi, S., Toda, T., Neubig, G., Sakti, S., Nakamura, S.: Prosody-controllable HMM-based speech synthesis using speech input. In: Proceedings of the MLSLP (2015)

5. Nose, T., Kato, Y., Kobayashi, T.: Style estimation of speech based on multiple regression hidden semi-Markov model. In: Proceedings of the INTERSPEECH, pp. 2285–2288 (2007)

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