Speech Enhancement Based on Filtering the Spectrotemporal Modulations
Nima Mesgarani, Shihab Shamma · 2006
A monaural noise suppression algorithm is proposed based on filtering the spectrotemporal modulations of noisy speech. The modulations are estimated from a multiscale representation of the signal spectrogram generated by a model of sound processing in the auditory system. A significant advantage of this method is its ability to suppress noise that has distinctive modulation patterns, despite being spectrally overlapping with the speech. The performance of the algorithm is evaluated using subjective and objective tests and compared to the optimal smoothing and minimum statistics approach (Martin (2001)). The results demonstrate the efficacy of the spectrotemporal filtering approach in the conditions examined.