首页> 外文会议>International Conference on Spoken Language Processing; 20041004-08; Jeju(KR) >Efficient Vector Quantisation of Line Spectral Frequencies Using the Switched Split Vector Quantiser
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Efficient Vector Quantisation of Line Spectral Frequencies Using the Switched Split Vector Quantiser

机译:使用切换的分割矢量量化器对线谱频率进行有效的矢量量化

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In this paper, we investigate the use of a switched split vector quantiser (SSVQ) for coding linear predictive coding (LPC) parameters. The SSVQ is applied to quantise the LPC parameters in terms of line spectral frequencies from the TIMIT database and its performance is compared with the split vector quantiser. Experimental results show that the SSVQ provides a better trade-off between bit-rate and distortion performance than the split VQ. In addition, the SSVQ has a lower computational (search) complexity than the split VQ, though this is attained at the expense of an increase in memory requirements. In order to achieve a spectral distortion of 1 dB, the three-part SSVQ with an 8 directional switch requires 23 bits/frame, 4.41 kflops/frame of computations and 8272 floats of memory, while the corresponding values for a traditional three-part split VQ are 25 bits/frame, 13.3 kflops/frame and 3328 floats, respectively.
机译:在本文中,我们研究了使用转换分割矢量量化器(SSVQ)来编码线性预测编码(LPC)参数。 SSVQ用于根据TIMIT数据库中的线频谱频率对LPC参数进行量化,并将其性能与分离矢量量化器进行比较。实验结果表明,SSVQ比分离的VQ在比特率和失真性能之间提供了更好的权衡。此外,SSVQ的计算(搜索)复杂度比拆分的VQ低,尽管这样做的代价是增加了内存需求。为了实现1 dB的频谱失真,带有8个方向开关的三部分SSVQ需要23位/帧,4.41 kflops /帧的计算和8272个存储器浮点数,而传统的三部分拆分的对应值VQ分别为25位/帧,13.3 kflops /帧和3328浮点数。

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