Harmonic-Temporal Clustering of Speech for Single and Multiple F0 Contour Estimation in Noisy Environments
Jonathan Le Roux, Hirokazu Kameoka, Nobutaka Ono, Alain de Cheveigné, Shigeki Sagayama · 2007
We present in this paper a novel F0contour estimation method based on a parametric description of the wavelet power spectrum of speech that accounts for its structure simultaneously in time and frequency directions. We model the speech spectrum as a sequence of spectral clusters governed by a smooth common F0contour expressed as a spline curve. The harmonic and temporal structure of these clusters and their common F0contour are estimated simultaneously. Through experimental comparisons with existing methods, we show that our algorithm is competitive on clean single-speaker speech, and that it outperforms existing methods both in the presence of noise and for the estimation of multiple F0contours of cochannel concurrent speech.