Speech Compression and Reconstruction Based on Adaptive Multiscale Compressed Sensing Theory

SUN Lin-hui; YANG Zhen; YE Lei

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Speech Compression and Reconstruction Based on Adaptive Multiscale Compressed Sensing Theory

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- Speech Compression and Reconstruction Based on Adaptive Multiscale Compressed Sensing Theory
- Acta Electronica Sinica Vol. 39, Issue 1, Pages: 40-45(2011)
- 作者机构：
  
  南京邮电大学通信与信息工程学院,江苏,南京,210003
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN912.3
- Published：2011
- 稿件说明：
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SUN Lin-hui, YANG Zhen, YE Lei. Speech Compression and Reconstruction Based on Adaptive Multiscale Compressed Sensing Theory[J]. Acta Electronica Sinica, 2011, 39(1): 40-45.
DOI：

SUN Lin-hui, YANG Zhen, YE Lei. Speech Compression and Reconstruction Based on Adaptive Multiscale Compressed Sensing Theory[J]. Acta Electronica Sinica, 2011, 39(1): 40-45. DOI：

摘要

本文针对语音信号的压缩感知问题

在系数总长度不超过原信号长度的前提下

推导了Sym小波分解合成的矩阵形式

提出了语音信号多尺度压缩感知(MCS)框架.进一步分析语音信号在小波基下不同级的稀疏性

提出了自适应多尺度压缩感知(AMCS)方法

把该方法运用到语音压缩与重构中

对重构语音进行了主客观评价

并进行了说话人识别验证

得出结论:基于AMCS比三层MCS重构语音的性能好.

Abstract

In this paper

a matrix form of Sym wavelet decomposition and synthesis is deduced

keeping the length of the coefficient no more than the length of original speech signals

and then we propose a framework of speech Multiscale Compressed Sensing (MCS) and an Adaptive Multiscale Compressed Sensing (AMCS) method by analyzing sparsity of different wavelet levels of speech signals .We compare AMCS with MCS by applying both methods to speech compression and reconstruction

and the reconstructed speech signal evaluated by the objective and subjective evaluation is applied to speaker recognition.The experimental results show that the reconstruction performance of speech signal based on AMCS is superior to MCS.

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