In this paper, we propose a signal-channel speech enhancement algorithm by applying the conventional Wiener filter in the spectro-temporal modulation domain. The multi-resolution spectro-temporal analysis and synthesis framework for Fourier spectrograms [12] is extended to the analysis-modification-synthesis (AMS) framework for speech enhancement. Compared with conventional speech enhancement algorithms, a Wiener filter and an extended minimum mean-square error (MMSE) algorithm, our proposed method outperforms them by a large/small margin in white/babble noise conditions from both objective and subjective evaluations.
['Chung-Chien Hsu', 'Tse-En Lin', 'Jian-Hueng Chen', 'Tai-Shih Chi']
Spectro-temporal subband Wiener filter for speech enhancement