Bases théoriques et expérimentales pour une nouvelle méthode de séparation des composantes pseudo-harmoniques et bruitées de la parole
In this paper, the problem of separating the harmonic and noise components of speech signals is addressed. A new method is proposed, based on two specific processes dedicated to better take into account the non-stationarity of speech signals: first, a period-scaled synchronous analysis of spectral parameters (amplitudes and phases) is done, referring to the Fourier series expansion of the signal, as opposed here to the typically used Short-Term Fourier Transform (STFT). Second, the separation itself is based on a low-pass filtering of the parameters trajectory. Preliminary experiments on synthetic speech show that the proposed method has the potential to significantly outperform a reference method based on STFT: Signal-to-error ratio gains of 5 dB are typically obtained. Conditions to go beyond the theoretical framework towards more practical applications on real speech signals are discussed.