research-article

FLD-based detection of re-compressed speech signals

Authors:

Xiaoying Feng,

Gwenaël DoërrAuthors Info & Claims

MM&Sec '10: Proceedings of the 12th ACM workshop on Multimedia and security

Pages 43 - 48

https://doi.org/10.1145/1854229.1854239

Published: 09 September 2010 Publication History

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Abstract

Prior works on re-quantization detection were mainly focused on still images and videos, implying that the involved quantization is uniform. In this paper, we examine non-uniform re-quantization, and then investigate the automatic detection of re-compressed speech signals. Based on Fisher Linear Discriminant (FLD), two detection algorithms are described in the time-domain and in the DFT-domain respectively. Comparative experiments indicate that both detection algorithms produce reliable results with AUC values higher than 0.9744 for a set of different experimental setups. In general, time-domain detection performs slightly better than DFT-domain detection. However, the latter is superior in the less dimensionality of input vectors.

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Cited By

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Luo DLuo WYang RHuang J(2012)Compression history identification for digital audio signal2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2012.6288233(1733-1736)Online publication date: Mar-2012
https://doi.org/10.1109/ICASSP.2012.6288233

Index Terms

FLD-based detection of re-compressed speech signals
1. Information systems
  1. Information systems applications

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Information & Contributors

Information

Published In

MM&Sec '10: Proceedings of the 12th ACM workshop on Multimedia and security

September 2010

264 pages

ISBN:9781450302869

DOI:10.1145/1854229

General Chair:
Patrizio Campisi
Università degli Studi Roma TRE, Rome, Italy
,
Program Chairs:
Jana Dittmann
Otto-von-Guericke University Magdeburg, Germany
,
Scott Craver
SUNY Binghamton, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 September 2010

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MM&Sec '10

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SIGMM

MM&Sec '10: Multimedia and Security Workshop

September 9 - 10, 2010

Roma, Italy

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Overall Acceptance Rate 128 of 318 submissions, 40%

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Luo DLuo WYang RHuang J(2012)Compression history identification for digital audio signal2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2012.6288233(1733-1736)Online publication date: Mar-2012
https://doi.org/10.1109/ICASSP.2012.6288233

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Cited By

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Recommendations

MFCC-GMM based accent recognition system for Telugu speech signals

Extracting Efficient Spectrograms From MP3 Compressed Speech Signals for Synthetic Speech Detection

Intelligibility of time-compressed synthetic speech