Noise robust Voice Activity Detection for multiple speakers
Jaime Lorenzo-Trueba, Nozomu Hamada · 2010
Many modern systems rely on transparent human-machine interfaces that allow them to fulfill their purpose in a more efficient and unobtrusive way. In order to build an efficient and reliable speech based human-machine interface, being able to determine when to process the incoming signals even in unfavorable environments is a definite requisite. Our Voice Activity Detection (VAD) method proposes a novel way of mixing monaural and microphone array techniques; monaural techniques are mainly focused on providing robusticity, while microphone array techniques complete the system with the capability of detecting source direction from background noise. This is implemented by first applying a cochlear filtering and channel selection to remove noise, and then a series of strict conditions are applied in order to be able to obtain the fundamental frequencies of the sources which is finally used to obtain the VAD masks.