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* Corresponding author. Abhishek verma

1M.Tech., Speech and Image Processing Lab, Indian Institute of Information Technology Allahabad 211012, Uttar Pradesh, India.

2Research Scholar, Speech and Image Processing Lab, Indian Institute of Information Technology Allahabad 211012, Uttar Pradesh, India.

3Professor,Department of Human-Computer Interaction, Indian Institute of Information Technology Allahabad 211012, Uttar Pradesh, India

Abstract

Keywords: Digital speech Tampering, Copy-Move Forgery, Audio Features, Neighbor Shift matching

1. Introduction


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Types of forgery in the audio contents

Insertion: Copy-Move:

Deletion: Substitution: Splicing:

Previous work


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A assive pproach to etect opyMve orgery in igital peech udioignal

2. Features Used

Root mean square value (RMS value): -


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Zero-crossing rate (ZCR): T

Spectral Flatness measure (SFM) :

Spectral Crest Factor (SCF):

Mel-Frequency Cepstral Coefficients (MFCC):

Power Spectral Density (Spectra Density Mean and Spectral Density Standard Deviation):


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A assive pproach to etect opy-ove orgery in igital peech udioignal

3. Proposed Method

.

DownSampling (Optional):-

Windowing of samples:-


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Feature Extraction/computation

.

Lexicographical Sorting:-


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Detection of suspected copied region:-

Neighbor Shift matching: -

.

.

Detection and marking of Duplicated Region:-


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3.1 Algorithm-copy-move forgery detection of digital audio speech signal:-

.

Begin

End

4. Experimental result/Description


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guess the question from

the answers guess the question from the answersguess

.


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5. Conclusion

Acknowledgement:

References

Dr. Girija Chetty (Ed.)

International Journal of Advanced Science and Technology

IEEE signal processing magazine

4th International

Congress on Image and Signal Processing

Advances in

Computers

IEEEWorkshop on Applications of Signal Processing to Audio and Acoustics 2001

ACM 978-1-60558-

058,MM&Sec08

International Journal of

Electronics and telecommunications

IEEE,

ICASSP

J. Audio Eng. Soc.,

IEEE Computer Society

.

Features used Percentage of false matching pair


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ACM 978-1-59593-857-2

National Institute of Standards andTechnology, NISTIR 4930


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Index

A

Audio features, 186, 193

CCopy-move forgery, 184186, 188

detection algorithm, 191sample of, 185

D

Digital audiosdefine, 184

down sampling, 188

duplicated region, detection and marking of, 190experimental result/description, 191192feature extraction/computation, 189

flow chart, 188

lexicographical sorting, 189190MFCC, 187

neighbor shift matching, 190

PSD, 187root mean square value (RMS value), 186

SCF, 187188

SFM, 187188signal processing, 186188

suspected copied region, detection, 190windowing of samples, 188189

ZCR, 187

Digital forgery

define, 184types of, 185186

Digital speech tampering, 184

M

Mel-frequency cepstral coefficients (MFCC), 187

N

Neighbor shift matching, 185, 190


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P

Power spectral density (PSD), 187

R

Root mean square value (RMS value), 186

S

Spectral crest factor (SCF), 187188Spectral flatness measure (SFM), 187188

Z

Zero-crossing rate (ZCR), 187

session 02_paper 26

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