NDLI: Sound source detection using multiple noise models

Content Provider	IEEE Xplore Digital Library
Author	Matsunaga, S. Yamaguchi, M. Yamauchi, K. Yamashita, M.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. & Inf. Sci., Nagasaki Univ., Nagasaki (Matsunaga, S.; Yamaguchi, M.; Yamauchi, K.; Yamashita, M.)
Abstract	This paper describes a sound source detection approach based on elaborate noise-modeling techniques for audio indexing. For accurate detection, we devised two methods to generate multiple-noise models through clustering techniques. One method is based on frame-wise data similarity, and the other is based on noise source similarity. The former method employs K-means clustering and a smoothing technique to avoid inaccurate segmentation. The latter method involves noise modeling based on a tree data structure generated by the progressive merging of noise clusters. The classification experiments show that by using these proposed methods, audio sources can be detected with better accuracy than that achieved by a conventional method. When four noise models generated by the latter method were used, the noise detection performance increased by 3.9% for the periods in which the sound sources did not overlap. With regard to the experiments for an audio stream that included overlapped segments, the noise detection performance increased by 1.2% without a decrease in the speech detection performance.
Starting Page	2025
Ending Page	2028
File Size	256002
Page Count	4
File Format	PDF
ISBN	9781424414833
ISSN	15206149
DOI	10.1109/ICASSP.2008.4518037
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Acoustic noise Acoustic signal detection Indexing Speech recognition Noise generators Streaming media Speech enhancement Smoothing methods Multimedia communication Tree data structures Acoustic segmentation Clustering
Content Type	Text
Resource Type	Article

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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