Multi-microphone speech enhancement informed by auditory scene analysis

A multitude of multi-microphone speech enhancement methods is available. In this paper, we focus our attention to the well-known minimum variance distortionless response (MVDR) beamformer, due to its ability to preserve distortionless response towards the desired speaker while minimizing the output noise power. We explore two alternatives for constructing the steering vectors towards the desired speech source. One is only using the direct path of the speech propagation in the form of delay-only filters, while the other is using the entire room impulse response (RIR). All beamforming methods requires some control information to be able to accomplish the task of enhancing a desired speech signal. In this paper, an acoustic event detection method using biologically-inspired features is employed. It can interpret the auditory scene by detecting the presence of different auditory objects. This is employed to control the estimation procedures used by beamformer. The resulting system provides a blind method of speech enhancement that can improve intelligibility independently of any additional information. Experiments with real recordings show the practical applicability of the method. Significant gain in fwSNRseg is achieved. Compared to using the direct path only, the use of the entire RIR proves beneficial.