Context-Based Adaptive Arithmetic Encoding of EAVQ Indices

This paper presents a lossless compression algorithm for the binary indices of the embedded algebraic vector quantizer (EAVQ) used by the AMR-WB (Extended Adaptive Multi-Rate Wide Band) codec. We present a statical study of the EAVQ indices for diverse audio types (speech, music, etc.) and we discuss the design of the lossless algorithm including the choice of different strategies. The proposed algorithm combines run length encoding (RLE) and context-based arithmetic encoding to reduce the bitrate of the EAVQ indices by about 10% at the expense of 1% rise in complexity of the codec. The proposed algorithm can increase the segmental signal to noise ratio of about 9% at low rates for speech signals and improve the subjective scores in noisy channels by about 0.5 on a five-point scale if combined with an additional protection layer.

[1]  Roch Lefebvre,et al.  The adaptive multirate wideband speech codec (AMR-WB) , 2002, IEEE Trans. Speech Audio Process..

[2]  Eric Bodden,et al.  Arithmetic Coding revealed A guided tour from theory to praxis. , 2004 .

[3]  Roch Lefebvre,et al.  Low-complexity multi-rate lattice vector quantization with application to wideband TCX speech coding at 32 kbit/s , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4]  Robert G. Gallager,et al.  Variations on a theme by Huffman , 1978, IEEE Trans. Inf. Theory.

[5]  J. Pieter M. Schalkwijk,et al.  An algorithm for source coding , 1972, IEEE Trans. Inf. Theory.

[6]  Roch Lefebvre,et al.  Extended AMR-WB for high-quality audio on mobile devices , 2006, IEEE Communications Magazine.

[7]  Jean-Pierre Adoul,et al.  8 kbit/s ACELP coding of speech with 10 ms speech-frame: a candidate for CCITT standardization , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[8]  N. J. A. Sloane,et al.  Fast quantizing and decoding and algorithms for lattice quantizers and codes , 1982, IEEE Trans. Inf. Theory.

[9]  Giovanni Manzini,et al.  The Burrows-Wheeler Transform : Theory and Practice , 1999 .

[10]  Minjie Xie,et al.  Embedded algebraic vector quantizers (EAVQ) with application to wideband speech coding , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[11]  Khalid Sayood,et al.  Introduction to data compression (2nd ed.) , 2000 .

[12]  N. J. A. Sloane,et al.  A fast encoding method for lattice codes and quantizers , 1983, IEEE Trans. Inf. Theory.

[13]  Philippe Gournay.  A Very Low Bit Rate Protection Layer to Increase the Robustness of the AMR-WB+ Codec against Bit Errors , 2007 .

[14]  Jean-Pierre Adoul,et al.  Algorithme de quantification vectorielle sphérique à partir du réseau de Gosset d’ordre 8 , 1988 .

[15]  G. Blelloch.  Introduction to Data Compression * , 2022 .

[16]  David A. Huffman,et al.  A method for the construction of minimum-redundancy codes , 1952, Proceedings of the IRE.