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Fault Detection in a Microphone Array by Intercorrelation of Features in Voice Activity Detection

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2 Author(s)
Jinsung Kim ; Department of Electrical Engineering, Korea University, Seoul, Korea ; Bum-Jae You

Voice-based interaction generates a lot of interest for natural human-robot interaction. Auditory information from microphones is an essential clue for a robot's attention to a person. Fault detection of microphones is required in order to improve the reliability of the voice-based human-robot interaction. This paper proposes a new approach for real-time fault detection in a microphone array in conversation without a calibration signal and a known sound source position by the intercorrelation of features in voice activity detection. The approach is successfully applied to a six-microphone system, and experimental results show an average fault detection of 97.6%.

Published in:

IEEE Transactions on Industrial Electronics  (Volume:58 ,  Issue: 6 )