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Embedded quantization of line spectral frequencies using a multistage tree-structured vector quantizer

机译:使用多级树结构矢量量化器对线频谱频率进行嵌入式量化

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This paper presents a multistage tree-structured vector quantization (MTVQ) scheme for line spectral frequencies (LSF), where two advantages exist: It supports embedded quantization which is required for scalable coder designs, and the tree-structure at each stage can be relied on to accelerate the encoding process. The different codebook design strategies suitable for MTVQ are analyzed. Two speech coding standards are modified by replacing their original LSF quantizers with an MTVQ; it is shown that graceful quality degradation can be obtained for the synthetic speech when the number of bits available for LSF decoding is decremented one-by-one. Moreover, the search complexity is substantially reduced with slight performance degradation.
机译:本文提出了一种用于线谱频率(LSF)的多级树结构矢量量化(MTVQ)方案,该方案存在两个优点:它支持可伸缩编码器设计所需的嵌入式量化,并且可以依赖每一级的树结构加快编码过程。分析了适用于MTVQ的不同密码本设计策略。通过用MTVQ替换它们的原始LSF量化器,可以修改两个语音编码标准。结果表明,当可用于LSF解码的比特数一一递减时,对于合成语音可以获得适度的质量下降。而且,搜索复杂度大大降低,性能略有下降。

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