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The increasing availability of forensic audio surveillance recordingsa covering days or weeks of time makes human audition impractical. This paper describes the rationale and potential application of several techniques for high-speed automated search and
Author (s): Robert C. Maher, Joseph Studniarz;
Affiliation:
Montana State University, Bozeman, MT, USA
(See document for exact affiliation information.)
Publication Date:
2012-06-06
Session subject:
Miscellaneous Techniques
DOI:
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Robert C. Maher, Joseph Studniarz; 2012; Automatic Search and Classification of Sound Sources in Long-Term Surveillance Recordings [PDF]; Montana State University, Bozeman, MT, USA; Paper 6-3; Available from: https://aes.org/publications/elibrary-page/?id=16340
Robert C. Maher, Joseph Studniarz; Automatic Search and Classification of Sound Sources in Long-Term Surveillance Recordings [PDF]; Montana State University, Bozeman, MT, USA; Paper 6-3; 2012 Available: https://aes.org/publications/elibrary-page/?id=16340
@inproceedings{Robert2012automatic,
title={{Automatic Search and Classification of Sound Sources in Long-Term Surveillance Recordings}},
author={Robert C. Maher, Joseph Studniarz},
year={2012},
month={jun},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 6-3; AES Conference: 46th International Conference: Audio Forensics; June 2012},
number={6-3},
organization={AES},
}
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