Statistical F0 prediction for electrolaryngeal speech enhancement considering generative process of F0 contours within product of experts framework

Kou Tanaka; Hirokazu Kameoka; Tomoki Toda; Satoshi Nakamura

ICASSP 2016accepted0 citations

Statistical F0 prediction for electrolaryngeal speech enhancement considering generative process of F0 contours within product of experts framework

Kou Tanaka, Hirokazu Kameoka, Tomoki Toda, Satoshi Nakamura

Abstract

We have previously proposed a statistical fundamental frequency (F 0 ) prediction method that makes it possible to predict the underlying F 0 contour of electrolaryngeal (EL) speech from its spectral feature sequence. Although this method was shown to contribute to improving the naturalness of EL speech as a whole, the predicted F 0 contour was still unnatural compared with that in normal speech. One possible solution to improve the naturalness of the predicted F 0 contours would be to take account of the physical mechanism of vocal phonation. Recently a statistical model of voice F 0 contours was formulated by constructing a stochastic counterpart of the Fujisaki model, a well-founded mathematical model representing the control mechanism of vocal fold vibration. This paper proposes a Product-of-Experts model to incorporate this generative model of voice F 0 contours into the statistical F 0 prediction model. Based on the constructed model, we derive algorithms for parameter training and F 0 prediction. Experimental results revealed that the proposed method successfully outperformed our previously proposed method in terms of the naturalness of the predicted F 0 contours.

BibTeX

@inproceedings{icassp2016_statisticalf0pre,
  title = {Statistical F0 prediction for electrolaryngeal speech enhancement considering generative process of F0 contours within product of experts framework},
  author = {Kou Tanaka and Hirokazu Kameoka and Tomoki Toda and Satoshi Nakamura},
  booktitle = {ICASSP 2016},
  year = {2016}
}