压缩传感语音编算法.pdfVIP

摘要 摘 要 压缩传感是一种以远低于奈奎斯特频率对信号进行采集和压缩的新兴理论。 压缩传感首先采用非自适应线性投影来保持信号的原始结构，通过数值最优化问 题由这些投影信号来准确重构原始信号。 本文介绍了压缩传感理论框架，并对其中存在的难点问题进行了探讨。在此 基础上，结合现有的语音压缩编码算法，提出了一种基于压缩传感的语音压缩编 码算法。该算法基于语音信号的频域特性，根据信号高低频部分所携带的信息和 能量的差异，对高频系数和低频系数进行分别编码和解码，在保证一定的信号重 构质量的基础上，有效的对语音信号进行了压缩。此外，本文还提出了一种用于 语音信号传输的基于压缩传感的多描述编码算法。这个算法具有抗丢包能力强且 结构简单易实现的特点，对语音信号在DCT或MDCT域进行随机观测、量化、打包 形成多个描述码流。在接收端，解码器根据接收码流情况通过求解优化问题可以 近似或精确的重建原始语音信号。 本文对以上设计的算法从测量长度即压缩比、信号稀疏度，量化误差以及DCT 变换和MDCT 变换等方面对算法性能的影响进行了全面的性能测试，并用客观评 价方法 PESQ 对各种重构信号进行了评分。实验结果表明，基于压缩传感理论的 语音压缩算法能提供较高的压缩比，并且能够得到较小的压缩误差。基于压缩传 感的多描述编码方法可被用来在不可靠网络中实时传输音频信号，在不附加延迟 的基础上提供可靠的信源编码。 关键词 关键词 关关键键词词：语音压缩编码技术 压缩传感 重构算法 多描述编码 Abstract Abstract Compressive Sensing is a new theory that captures and represents compressible signals. It first employs non-adaptive linear projections that preserve the structure of the signal, and then the signal reconstruction is conducted using an optimization process from these projections. This paper introduces the theoretical framework of compressed sensing and discusses the existing difficult problems. Based on the analysis of the theoretics on compressed sensing and existing speech compressing coding methods, a new speech compressing coding algorithm using compressed sensing was presented. This algorithm is based on the characteristic of speech signal in frequency domain and the low frequency and high frequency coefficients were compressed respectively based on the information and energy they took. In addition, a new multiple description coding method for speech transmission was proposed. The method is robust to packet loss or bit error, and has the ad