Hybrid Method Using Wavelets and Predictive Method for Compression of Speech Signal
The development of the signal compression
algorithms is having compressive progress. These algorithms are
continuously improved by new tools and aim to reduce, an average,
the number of bits necessary to the signal representation by means of
minimizing the reconstruction error. The following article proposes
the compression of Arabic speech signal by a hybrid method
combining the wavelet transform and the linear prediction. The
adopted approach rests, on one hand, on the original signal
decomposition by ways of analysis filters, which is followed by the
compression stage, and on the other hand, on the application of the
order 5, as well as, the compression signal coefficients. The aim of
this approach is the estimation of the predicted error, which will be
coded and transmitted. The decoding operation is then used to
reconstitute the original signal. Thus, the adequate choice of the
bench of filters is useful to the transform in necessary to increase the
compression rate and induce an impercevable distortion from an
auditive point of view.
[1] Frédéric Truchetet, "Ondelettes pour le signal numérique," collection
traitement du signal, 1998, chap.4, 25-51.
[2] I. Daubechies, "Ten lectures on wavelets," society for industrial and
applied matematics 1992.
[3] Ankil Patel, Mark Tonkelowitz and Mike Vernal, "Lossless sound
compression using the discrete wavelet transform," 2002.
[4] René Boite, Hervé Bourlard, Thierry Dutoit, Jo├½l Hancq et Henri
Leich "Traitement de la parole," 2000 Presses plytechniques et
universitaires romandes, Collection électricité, chap. 2, pp 27-64.
[5] Stephane Mallat and Sifen Zhong , "Caracterization of signals from
multiscale edges", IEEE Transactions on pattern and machine
intelligence, Vol. 14, N┬░7, July 1992.
[6] Jalal Karam, Raed Saad "The Effect of Different compression schemes
on speech signals," International Journal of Biomedical Sciences
Volume 1 Number 4, 230-234.
[7] Jalal Karam, ÔÇÿVarious Speech Processing Techniques for Speech
Compression and Recognition", Proceeding of world academy of
science, engineering and technology volume 26 décember 2007 issn
1307-6884.
[8] Amhamed Saffor, Abdul Rahmen Ramli and Kwan-Hoong Ng
"A comparative study of image compression between JPEC and
wavelet," Malaysian Journal of computer science, volume 14 No. 1,
June 2001, pp 30-45.
[1] Frédéric Truchetet, "Ondelettes pour le signal numérique," collection
traitement du signal, 1998, chap.4, 25-51.
[2] I. Daubechies, "Ten lectures on wavelets," society for industrial and
applied matematics 1992.
[3] Ankil Patel, Mark Tonkelowitz and Mike Vernal, "Lossless sound
compression using the discrete wavelet transform," 2002.
[4] René Boite, Hervé Bourlard, Thierry Dutoit, Jo├½l Hancq et Henri
Leich "Traitement de la parole," 2000 Presses plytechniques et
universitaires romandes, Collection électricité, chap. 2, pp 27-64.
[5] Stephane Mallat and Sifen Zhong , "Caracterization of signals from
multiscale edges", IEEE Transactions on pattern and machine
intelligence, Vol. 14, N┬░7, July 1992.
[6] Jalal Karam, Raed Saad "The Effect of Different compression schemes
on speech signals," International Journal of Biomedical Sciences
Volume 1 Number 4, 230-234.
[7] Jalal Karam, ÔÇÿVarious Speech Processing Techniques for Speech
Compression and Recognition", Proceeding of world academy of
science, engineering and technology volume 26 décember 2007 issn
1307-6884.
[8] Amhamed Saffor, Abdul Rahmen Ramli and Kwan-Hoong Ng
"A comparative study of image compression between JPEC and
wavelet," Malaysian Journal of computer science, volume 14 No. 1,
June 2001, pp 30-45.
@article{"International Journal of Electrical, Electronic and Communication Sciences:52159", author = "Karima Siham Aoubid and Mohamed Boulemden", title = "Hybrid Method Using Wavelets and Predictive Method for Compression of Speech Signal", abstract = "The development of the signal compression
algorithms is having compressive progress. These algorithms are
continuously improved by new tools and aim to reduce, an average,
the number of bits necessary to the signal representation by means of
minimizing the reconstruction error. The following article proposes
the compression of Arabic speech signal by a hybrid method
combining the wavelet transform and the linear prediction. The
adopted approach rests, on one hand, on the original signal
decomposition by ways of analysis filters, which is followed by the
compression stage, and on the other hand, on the application of the
order 5, as well as, the compression signal coefficients. The aim of
this approach is the estimation of the predicted error, which will be
coded and transmitted. The decoding operation is then used to
reconstitute the original signal. Thus, the adequate choice of the
bench of filters is useful to the transform in necessary to increase the
compression rate and induce an impercevable distortion from an
auditive point of view.", keywords = "Compression, linear prediction analysis,multiresolution analysis, speech signal.", volume = "2", number = "4", pages = "545-4", }