Vector quantizationwith renormalized splits for wideband speech

M. A. Ramírez
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引用次数: 2

Abstract

A method is proposed for split vector quantization (SVQ) that, while keeping up with the lower search complexity inherent to SVQ, reduces the attendant split loss. It operates partially in the training and encoding phases by normalizing the bandwidth covered by each split. The action is completed in the decoding phase by renormalizing the bandwidth spanned by each split of the codebook to that allowed by a nonoverlapping constraint with neighboring split bands. Therefore, the method is referred to as renormalized SPV (RSVQ). The performance of RSVQ is investigated in comparison to standard SVQ for coding line spectral frequency (LSF) vectors that parameterize the spectral envelope of wideband speech and it is found to save four bits, reaching transparent coding at 42 bit/frame.
宽带语音重归一化分割的矢量量化
提出了一种分割向量量化(SVQ)方法,在保持SVQ固有的较低搜索复杂度的同时,减少了分割损失。它通过对每个分割所覆盖的带宽进行归一化,部分地在训练和编码阶段进行操作。通过将码本的每次分割所跨越的带宽重新规格化为与相邻分割带的非重叠约束所允许的带宽,该操作在解码阶段完成。因此,该方法被称为重归一化SPV (RSVQ)。研究了RSVQ与标准SVQ在编码参数化宽带语音频谱包络线谱频率(LSF)矢量时的性能,发现RSVQ可以节省4比特,达到42比特/帧的透明编码。
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