Title :
Noise robust Voice Activity Detection for multiple speakers
Author :
Lorenzo-Trueba, Jaime ; Hamada, Nozomu
Author_Institution :
Signal Process. Lab., Keio Univ., Yokohama, Japan
Abstract :
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.
Keywords :
filtering theory; man-machine systems; microphone arrays; signal detection; speaker recognition; background noise; channel selection; cochlear filtering; human-machine interface; microphone array; monaural array; multiple speaker; noise robust voice activity detection; source direction detection; speech reliability; Compounds; Harmonic analysis; Power harmonic filters;
Conference_Titel :
Intelligent Signal Processing and Communication Systems (ISPACS), 2010 International Symposium on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-7369-4
DOI :
10.1109/ISPACS.2010.5704658