Improving the Switched Split Vector Quantization Technique using a Joint Source Channel Coding Approach
Main Article Content
Abstract
This paper deals with enhancing the error resilient of the Switched Split Vector Quantization (SSVQ) techniques by adopting the optimal Index Assignment approach, a Joint Source-Channel coding method. SSVQ is one of the latest structured vector quantization schemes and it has several advantages over other schemes. The new method proposed in this paper can improve the SSVQ encoder without the addition of extra bits and coding complexity. In addition, the application of the new method in speech coding is also investigated in this paper. The effectiveness of IA-SSVQ method is validated by comparing it with other methods through simulations.
Keywords
Joint Source-Channel coding, Vector Quantization, Index Assignment, Switched Split Vector Quantization
Article Details
References
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[12] K. Zeger and A. Gersho, Pseudo-Gray Coding, IEEE Trans. on Commun., 38(12) (1990) 2147-2158.
[13] T.N. Tuan, N.Q. Trung, Improving the Simulated Annealing algorithm for the Index Assignment method to enhance the robustness of communication systems, Vietnamese Journal on Inf. Tech. & Comm.., E-3, 7(11) (2014) 13-20.
[14] A. M. Kondoz, Digital Speech: Coding for Low Bit Rate Communication Systems, 2nd Edition, John Wiley and Sons, 2004.
[15] F. Itakura, Line spectrum representation of linear predictive coefficients of speech signals, J. Acoust. Soc. Amer., 57 (1975) S35.
[16] ITU-T Recommendation G.722.2, Wideband Coding of Speech at Around 16 kb/s Using Adaptive Muti- rate Wideband (AMR-WB), 2003.
[17] J. Garofol and al., Darpa TIMIT, Acoustic-Phonetic Continuous Speech Corpus CD-ROM, National Institute of Standards and Technology, NISTIR 493, USA, 1990.
[2] T.D. Lookabaugh, R.M. Gray, High-resolution quantization theory and the vector quantizer advantage, IEEE Trans. Inform. Theory 35 (5) (1989) 1020-1033.
[3] S. So, K.K. Paliwal, Efficient vector quantisation of line spectral frequencies using the switched split vector quantiser, Proc. Int. Conf. Spoken Language Processing, Korea, 2004.
[4] S. So, K.K. Paliwal, Switched Split Vector Quantisation of Line Spectral Frequencies for Wideband Speech Coding, INTERSPEECH-2005, Portugal, (2005) 2705-2708.
[5] S. So, K.K. Paliwal, Efficient product code vector quantization using switched split vector quantizer, Digital Signal Processing journal, Elsevier, 17(1) (2007) 138-171.
[6] S. So, K. K. Paliwal, A Comparative Study of LPC Parameter Representations and Quantisation Schemes for Wideband Speech Coding, Digital Signal Processing Journal, Elsevier, 17(1) (2007) 114-137.
[7] M. Bouzid, S. Cheraitia, Channel Optimized Switched Split Vector Quantization for Wideband Speech LSF Parameters, Proc. 11th Int. Conf. on Inf. Science, ISSPA2012, Canada, (2012) 1045-1050.
[8] N. Farvadin, A Study of Vector Quantization for Noisy Channels, IEEE Trans. on Inf. Theory, 36(4) (1990) 799-809.
[9] N. Farvardin, V. Vaishampayan, On the performance and complexity of channel-optimized vector quantizers, IEEE Trans. Inf. Theory, 37(1) (1991) 155-160.
[10] Y. Linde, A. Buzo, and R. M. Gray, An algorithm for vector quantization design, IEEE Trans. on Commun., COM-28 (1980) 84-95.
[11] K. K. Paliwal, B. S. Atal, Efficient vector quantization of LPC parameters at 24 bits/frame, IEEE Transactions on Speech and Audio Processing, 1(1) (1993) 3-14.
[12] K. Zeger and A. Gersho, Pseudo-Gray Coding, IEEE Trans. on Commun., 38(12) (1990) 2147-2158.
[13] T.N. Tuan, N.Q. Trung, Improving the Simulated Annealing algorithm for the Index Assignment method to enhance the robustness of communication systems, Vietnamese Journal on Inf. Tech. & Comm.., E-3, 7(11) (2014) 13-20.
[14] A. M. Kondoz, Digital Speech: Coding for Low Bit Rate Communication Systems, 2nd Edition, John Wiley and Sons, 2004.
[15] F. Itakura, Line spectrum representation of linear predictive coefficients of speech signals, J. Acoust. Soc. Amer., 57 (1975) S35.
[16] ITU-T Recommendation G.722.2, Wideband Coding of Speech at Around 16 kb/s Using Adaptive Muti- rate Wideband (AMR-WB), 2003.
[17] J. Garofol and al., Darpa TIMIT, Acoustic-Phonetic Continuous Speech Corpus CD-ROM, National Institute of Standards and Technology, NISTIR 493, USA, 1990.