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Context-Based Adaptive Arithmetic Encoding of EAVQ Indices

机译:EAVQ指标的基于上下文的自适应算术编码

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This paper presents a lossless compression algorithm for the binary indices of the embedded algebraic vector quantizer (EAVQ) used by the AMR-WB${+}$ (Extendend 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.
机译:本文针对AMR-WB $ {+} $(扩展自适应多速率宽带)编解码器使用的嵌入式代数矢量量化器(EAVQ)的二进制索引提出了一种无损压缩算法。我们对各种音频类型(语音,音乐等)的EAVQ指标进行静态研究,并讨论无损算法的设计,包括选择不同的策略。所提出的算法结合了行程编码(RLE)和基于上下文的算术编码,以将EAVQ索引的比特率降低了约10%,而编解码器的复杂度却增加了1%。所提出的算法可以在低速率下将语音信号的分段信噪比提高约9%,并且如果与其他保护层结合使用,则可以在五点尺度上将嘈杂通道中的主观得分提高约0.5。

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