Model based abnormal acoustic source detection using a microphone array

Authors:
Heungkyu Lee;Jounghoon Beh;June Kim;Hanseok Ko
Affiliations:
Dept. of Visual Information Processing, Korea University, Seoul, Korea;Dept. of Electronics and Computer Engineering, Korea University, Seoul, Korea;Dept. of Information and Communication Engineering, Seokyeong University;Dept. of Electronics and Computer Engineering, Korea University, Seoul, Korea
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

Citing 0
Cited 1

Decision fusion of shape and motion information based on bayesian framework for moving object classification in image sequences

ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes the model based detection method of abnormal acoustic source using a microphone array. General source location algorithm using a microphone array can be used to locate a dominant acoustic source, while this does not verify whether the detected source is permitted one or not on outdoor environments. It is difficult to discern it among a natural environmental sound. Thus, to cope with this problem, we propose the out-of-normal acoustic rejection method based on N-best likelihood ratio test using natural environmental sound models. In order to evaluate the proposed algorithm, a real-time DSP was constructed, and experimental evaluation is described.