基于压缩感知的语音编码新方案

摘要

根据语音信号的稀疏性，将压缩感知理论应用于语音信号的处理中，提出了一种语音编码的新方案。该方法在编码端采用随机高斯矩阵对语音信号进行观测，得到较少的观测值，然后使用矢量量化编码进一步压缩数据；在解码端，通过矢量量化解码得到观测值，根据语音信号在离散余弦域中的稀疏性，用正交匹配追踪算法重构语音信号。所用算法，在保证语音信号重构质量的前提下降低计算复杂度，减小时延。实验结果表明，对于采样率为44100 Hz，量化位数为16 bit，码速率为705.6 kbps单声道语音信号压缩到100 kbps左右仍具有较好的语音质量，同时算法时间延迟低。%According to the sparse of the speech signal, applied compression perception theory to speech signal processing, this paper proposes a new scheme of speech signal coding. The method using random Gaussian matrix observing the speech signal on the encoding side , obtained fewer observations,then further compress the data using vector quantization coding.In the decoder, decoding by vector quantization, getting observations based on the speech signal sparsity in the discrete cosine domain, then reconstructed speech signal using orthogonal matching pursuit algorithm . The purpose of the algorithm is to reduce the computational complexity and delay on the premise of guarantee the quality of speech signal reconstruction. Experimental results show that the mono audio signal whose sampling rate is 44100 hz, quantitative is 16 bit and bit rate is 705.6 Kbps could be compressed to around 100 Kbps, the compressed speech signal still has good voice quality, at the same time the algorithm has lower time delay.