Scalable Hybrid Speech Codec for Voice over Internet Protocol Applications

With the advent of various web-based applications and the fourth generation (4G) access technology, there has been an exponential growth in the demand of multimedia service delivery along with speech signals in a voice over internet protocol (VoIP) setup. Need is felt to fine-tune the conventional speech codecs deployed to cater to the modern environment. This fine-tuning can be achieved by further compressing the speech signal and to utilize the available bandwidth to deliver other services. This paper presents a scalable -hybrid model of speech codec using ITU-T G.729 and db10 wavelet. The codec addresses the problem of compression of speech signal in VoIP setup. The performance comparison of the codec with the standard codec has been performed by statistical analysis of subjective, objective and quantifiable parameters of quality desirable from the codec deployed in VoIP platforms.

[1]  Mohamed Hesham Farouk.  Application of Wavelets in Speech Processing , 2014, Springer Briefs in Electrical and Computer Engineering.

[2]  S. Ferraz de Campos Neto,et al.  Performance of ITU-T G.729 8 kb/s CS-ACELP speech codec with nonvoice narrowband signals , 1997 .

[3]  V. Radha,et al.  A comparative study between Discrete Wavelet Transform and Linear Predictive Coding , 2012, 2012 World Congress on Information and Communication Technologies.

[4]  Redwan Salami,et al.  ITU-T G.729 Annex A: reduced complexity 8 kb/s CS-ACELP codec for digital simultaneous voice and data , 1997, IEEE Commun. Mag..

[5]  I. Daubechies.  Orthonormal bases of compactly supported wavelets , 1988 .

[6]  S. Hayashi,et al.  Design and description of CS-ACELP: a toll quality 8 kb/s speech coder , 1998, IEEE Trans. Speech Audio Process..

[7]  Manish Khare,et al.  Daubechies complex wavelet transform based approach for Multiclass object classification , 2014, The 2014 International Conference on Control, Automation and Information Sciences (ICCAIS 2014).

[8]  K. P. Soman,et al.  Insight into Wavelets: From Theory to Practice , 2005 .

[9]  Vishu Viswanathan,et al.  Real-Time Implementation of a Wavelet-Based Audio Coder on the TI TMS320C31 DSP Chip , 1994 .

[10]  Shijo M Joseph.  Spoken digit compression using Wavelet Packet , 2010, 2010 International Conference on Signal and Image Processing.

[11]  William J. Phillips,et al.  Optimal feature vector for speech recognition of unequally segmented spoken digits , 2000, 2000 Canadian Conference on Electrical and Computer Engineering. Conference Proceedings. Navigating to a New Era (Cat. No.00TH8492).

[12]  J. Srinonchat,et al.  Enhancement Speech Compression Technique Using Modern Wavelet Transforms , 2012, 2012 International Symposium on Computer, Consumer and Control.

[13]  Ali Ganoun,et al.  Spoken Arabic Digits Recognition Using Discrete Wavelet , 2014, 2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation.

[14]  K. Evans,et al.  Characterizing the subjective performance of the ITU-T 8 kb/s speech coding algorithm-ITU-T G.729 , 1997 .

[15]  Johnson I. Agbinya,et al.  Discrete wavelet transform techniques in speech processing , 1996, Proceedings of Digital Processing Applications (TENCON '96).

[16]  M. Jaber,et al.  SPEECH COMPRESSION USING WAVELETS , 2003 .

[17]  T.Acharya Kumar Ajoy Ray.  Information Technology : Principles and Applications , 2004 .

[18]  M.F. Fahmy,et al.  On the optimal choice of wavelet bases and signal compression using the wavelet lifting scheme , 2002, Proceedings of the Nineteenth National Radio Science Conference.

[19]  A. Ibrahim,et al.  Comparing speech compression using wavelets with other speech compression schemes , 2003, Proceedings. Student Conference on Research and Development, 2003. SCORED 2003..

[20]  Liam Kilmartin,et al.  The application of the wavelet transform for speech processing , 1993, EUROSPEECH.

[21]  P. Babu Anto,et al.  Speech Recognition of Isolated Malayalam Words Using Wavelet Features and Artificial Neural Network , 2008, 4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008).

[22]  G. Prasanna.  Speech Compression Using Wavelets , 2014 .

[23]  B. Goode,et al.  Voice over Internet protocol (VoIP) , 2002, Proc. IEEE.

[24]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[25]  Amir Sinaeepourfard,et al.  Comparison of VoIP and PSTN services by statistical analysis , 2011, 2011 IEEE Student Conference on Research and Development.

[26]  Benjamin W. Wah,et al.  Speech-and Network-Adaptive Layered G. 729 Coder for Loss Concealments of Real-Time Voice Over IP , 2005, 2005 IEEE 7th Workshop on Multimedia Signal Processing.

[27]  K. Poulose Jacob,et al.  A New Algorithm for Adaptive Smoothing of Signals in Speech Enhancement , 2013 .

[28]  Adnane Cherif,et al.  Optimized Speech Compression Algorithm Based on Wavelets Techniques and its Real Time Implementation on DSP , 2015 .

[29]  Truong Q. Nguyen,et al.  Wavelets and filter banks , 1996 .

[30]  Maoshen Jia,et al.  Speech enhancement using the combination of adaptive wavelet threshold and spectral subtraction based on wavelet packet decomposition , 2012, 2012 IEEE 11th International Conference on Signal Processing.

[31]  Mahesh Chandra,et al.  Speech Coding Techniques for VoIP Applications: A Technical Review , 2015 .