Identifying microphone from noisy recordings by using representative instance one class-classification approach

Vu, Huy Quan, Liu, Shaowu, Yang, Xinghua, Li, Zhi and Ren, Yongli 2012, Identifying microphone from noisy recordings by using representative instance one class-classification approach, Journal of networks, vol. 7, no. 6, pp. 908-917.

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Title Identifying microphone from noisy recordings by using representative instance one class-classification approach
Author(s) Vu, Huy Quan
Liu, Shaowu
Yang, Xinghua
Li, Zhi
Ren, Yongli
Journal name Journal of networks
Volume number 7
Issue number 6
Start page 908
End page 917
Total pages 10
Publisher Academy Publisher
Place of publication Oulu, Finland
Publication date 2012-06
ISSN 1796-2056
Keyword(s) machine Learning
data Mining
audio forensics
microphone forensics
one-class classification
Summary Rapid growth of technical developments has created huge challenges for microphone forensics - a sub-category of audio forensic science, because of the availability of numerous digital recording devices and massive amount of recording data. Demand for fast and efficient methods to assure integrity and authenticity of information is becoming more and more important in criminal investigation nowadays. Machine learning has emerged as an important technique to support audio analysis processes of microphone forensic practitioners. However, its application to real life situations using supervised learning is still facing great challenges due to expensiveness in collecting data and updating system. In this paper, we introduce a new machine learning approach which is called One-class Classification (OCC) to be applied to microphone forensics; we demonstrate its capability on a corpus of audio samples collected from several microphones. In addition, we propose a representative instance classification framework (RICF) that can effectively improve performance of OCC algorithms for recording signal with noise. Experiment results and analysis indicate that OCC has the potential to benefit microphone forensic practitioners in developing new tools and techniques for effective and efficient analysis.
Language eng
Field of Research 109999 Technology not elsewhere classified
Socio Economic Objective 970110 Expanding Knowledge in Technology
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2012, Academy Publishers
Persistent URL http://hdl.handle.net/10536/DRO/DU:30046977

Document type: Journal Article
Collection: School of Information Technology
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