Harmonic beamformers for speech enhancement and dereverberation in the time domain

This paper presents a framework for parametric broadband beamforming that exploits the frequency-domain sparsity of voiced speech to achieve more noise reduction than traditional nonparametric broadband beamforming without introducing additional distortion. In this framework, the harmonic model is used to parametrize the signal of interest by a single parameter, the fundamental frequency, whereby both speech enhancement and derevereration can be performed. This framework thus exploits both the spatial and temporal properties of speech signals simultaneously and includes both fixed and adaptive beamformers, such as (1) delay-and-sum, (2) null forming, (3) Wiener, (4) minimum variance distortionless response (MVDR), and (5) linearly constrained minimum variance beamformers. Moreover, the framework contains standard broadband beamforming as a special case, whereby the proposed beamformers can also handle unvoiced speech. The reported experimental results demonstrate the capabilities of the proposed framework to perform both speech enhancement and dereverberation simultaneously. The proposed beamformers are evaluated in terms of speech distortion and objective measures for speech quality and speech intelligibility, and are compared to nonparametric broadband beamformers. The results show that the proposed beamformers perform well compared to traditional methods, including a state-of-the-art dereverberation method, particularly in adverse conditions with high amounts of noise and reverberation.