Joint acoustic and spectral modeling for speech dereverberation using non-negative representations

This paper proposes a single-channel speech dereverberation method enhancing the spectrum of the reverberant speech signal. The proposed method uses a non-negative approximation of the convolutive transfer function (N-CTF) to simultaneously estimate the magnitude spectrograms of the speech signal and the room impulse response (RIR). To utilize the speech spectral structure, we propose to model the speech spectrum using non-negative matrix factorization, which is directly used in the N-CTF model resulting in a new cost function. We derive new estimators for the parameters by minimizing the obtained cost function. Additionally, to investigate the effect of the speech temporal dynamics for dereverberation, we use a frame stacking method and derive optimal estimators. Experiments are performed for two measured RIRs and the performance of the proposed method is compared to the performance of a state-of-the-art dereverberation method enhancing the speech spectrum. Experimental results show that the proposed method improved instrumental speech quality measures, where using speech temporal dynamics was found to be beneficial in severe reverberation conditions.