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Techniques of using a microphone array to determine a sound source location, the localization problem, has been studied for many years. A popular method is the so-called MUSIC (Multiple Signal Classification). There is a second type of method that tries to solve both sound separation and localization problems in one setting. The second method used for localization purpose is less known. In this study,...
In this paper, a subband minimum classification error beamforming (S-MCEBEAM), instead of the subband likelihood maximizing beamforming (S-LIMABEAM) proposed by Seltzer, is investigated to closely integrate microphone array and speech recognizer for robust speech recognition in reverberant environments. The main idea behind this is to apply minimum classification error (MCE) criterion to directly...
In this paper, we propose a novel method for tracking two talkers. The tracking is performed using a microphone array and is based on algorithms implemented successively, namely, the PAST (Projection Approximation Subspace Tracking) and IPLS (Interior Point Least Square) algorithms. When multiple sound sources exist, the order of eigenvectors estimated by the PAST might change at each point in the...
In the paper, the authors propose a security monitoring system that can detect and classify the location and nature of different sounds within a room. This system is reliable and robust even in the presence of reverberation and in low signal-to-noise (SNR) environments. We describe a novel algorithm for audio classification, which, first, classifies an audio segment as speech or nonspeech and, second,...
This paper proposes a security-monitoring instrument that can detect and classify the location and nature of different sounds in a room. The instrument is reliable and robust even in the presence of reverberation and in low signal to noise ratio conditions. This paper proposes a new algorithm for classifying first an audio segment as speech or nonspeech then classifies the nonspeech audio segment...
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