采用自适应增益形状矢量量化的混合低比特率音频编码

S. Mehrotra, Weig-Ge Chen, K. Koishida, Naveen Thumpudi
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引用次数: 2

摘要

低比特率的音频编码通常会受到带宽截断引起的伪影的影响。在本文中,我们提出了一种以低比特率编码音频信号的新方案,该方案使用传统的标量量化和熵编码来编码频谱的某些部分(通常是较低的部分)。频谱的其他部分(通常是较高的部分)使用自适应增益形状矢量量化器以低比特率编码,其中用于矢量量化的码本由已经编码的频谱部分的未修改或修改版本形成。固定的预训练密码本也可用于某些情况下。这种方案的使用产生的音频编解码器已被证明是在低比特率下可用的最佳音频编解码器之一。此外,这种音频编解码器的解码器复杂性在低比特率下明显低于任何其他同等质量的编解码器。
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Hybrid low bitrate audio coding using adaptive gain shape vector quantization
Audio coding at low bitrates typically suffers from artifacts caused by bandwidth truncation. In this paper we present a novel scheme to code audio signals at low bitrates which uses a traditional scalar quantization followed by entropy coding to code some portions of the spectrum (typically the lower portion). The other portions (typically the higher portions) of the spectrum are coded at a low bitrate using an adaptive gain shape vector quantizer where the codebook for vector quantization is formed by unmodified or modified versions of the portions of the spectrum which have already been coded. Fixed pre-trained codebooks are also available for use in certain cases. The use of such a scheme results in an audio codec which has been shown to be among the best audio codecs available at low bitrates. In addition, the decoder complexity of this audio codec is significantly lower than any other codec of equal quality at low bitrates.
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