Narrowband Speech Hiding using Vector Quantization
In this work we introduce an efficient method to limit
the impact of the hiding process on the quality of the cover speech.
Vector quantization of the speech spectral information reduces drastically
the number of the secret speech parameters to be embedded
in the cover signal. Compared to scalar hiding, vector quantization
hiding technique provides a stego signal that is indistinguishable from
the cover speech. The objective and subjective performance measures
reveal that the current hiding technique attracts no suspicion about the
presence of the secret message in the stego speech, while being able
to recover an intelligible copy of the secret message at the receiver
side.
[1] N. Johnson and S. Jajodia, "Exploring steganography: seeing the unseen,"
IEEE Computer, pp. 26-34, February 1998.
[2] Eugene T. Lin and Edward J. Delp "A review of data hiding in digital
images", Proceedings of the Image Processing, Image Quality, Image
Capture Systems Conference, PICS-99
[3] T. Rabie, A Novel Compression Technique for Super Resolution Color
Photography, IEEE International Conference on Innovations in Information
Technology (IIT2006), November 2006. Dubai, UAE, 1-5.
[4] D. Guerchi, H. M. Harmain, T. Rabie, and E. E. Mohamed, "Speech Secrecy:
An FFT-based Approach," Special Issue on "Evolving Computer
Science Applications" of the Journal of Mathematics and Computer
Science, 3, n.2, pp. 107-125, 2008.
[5] D. Guerchi, "LPC-based Narrowband Speech Steganography," Journal
of Multimedia. (To appear.)
[6] D. O-Shaughnessy, "Speech Communications: Human and Machine,"
Wiley-IEEE Press; 2 edition, 1999.
[7] F. Itakura, "Line spectrum representation of linear predictive coefficients,"
Journal of Acoustics Society of America, vol. 57, no. 1, pp.
S35, 1975.
[1] N. Johnson and S. Jajodia, "Exploring steganography: seeing the unseen,"
IEEE Computer, pp. 26-34, February 1998.
[2] Eugene T. Lin and Edward J. Delp "A review of data hiding in digital
images", Proceedings of the Image Processing, Image Quality, Image
Capture Systems Conference, PICS-99
[3] T. Rabie, A Novel Compression Technique for Super Resolution Color
Photography, IEEE International Conference on Innovations in Information
Technology (IIT2006), November 2006. Dubai, UAE, 1-5.
[4] D. Guerchi, H. M. Harmain, T. Rabie, and E. E. Mohamed, "Speech Secrecy:
An FFT-based Approach," Special Issue on "Evolving Computer
Science Applications" of the Journal of Mathematics and Computer
Science, 3, n.2, pp. 107-125, 2008.
[5] D. Guerchi, "LPC-based Narrowband Speech Steganography," Journal
of Multimedia. (To appear.)
[6] D. O-Shaughnessy, "Speech Communications: Human and Machine,"
Wiley-IEEE Press; 2 edition, 1999.
[7] F. Itakura, "Line spectrum representation of linear predictive coefficients,"
Journal of Acoustics Society of America, vol. 57, no. 1, pp.
S35, 1975.
@article{"International Journal of Electrical, Electronic and Communication Sciences:61093", author = "Driss Guerchi and Fatiha Djebbar", title = "Narrowband Speech Hiding using Vector Quantization", abstract = "In this work we introduce an efficient method to limit
the impact of the hiding process on the quality of the cover speech.
Vector quantization of the speech spectral information reduces drastically
the number of the secret speech parameters to be embedded
in the cover signal. Compared to scalar hiding, vector quantization
hiding technique provides a stego signal that is indistinguishable from
the cover speech. The objective and subjective performance measures
reveal that the current hiding technique attracts no suspicion about the
presence of the secret message in the stego speech, while being able
to recover an intelligible copy of the secret message at the receiver
side.", keywords = "Speech steganography, LSF vector quantization, fast
Fourier transform", volume = "3", number = "5", pages = "1209-4", }