针对语音压缩编码技术中的关键问题,结合小波变换和最小绝对收缩和选择(Least Absolute Shrinkage and Selection Operator,LASSO)算法提出一种基于稀疏表示的语音压缩方法.首先,研究稀疏表示方法在语音压缩编码中的总体框架.其次,重点研究小波变换和LASSO算法在优化稀疏表示中的作用.最后,通过实验测试验证所提方法的有效性和优越性.实验结果表明,基于小波变换和LASSO的稀疏表示方法在语音压缩编码中获得更高的压缩比,为语音通信和存储提供了可靠的技术支持.
Research on Speech Compression Coding Technology Based on Sparse Representation
In response to the key issues in speech compression coding technology,combining wavelet transform and Least Absolute Shrinkage and Selection Operator(LASSO)algorithm,proposes a speech compression method based on sparse representation.Firstly,study the overall framework of sparse representation methods in speech compression coding.Secondly,the focus is on the role of wavelet transform and LASSO algorithm in optimizing sparse representation.Finally,the effectiveness and superiority of the proposed method were verified through experimental testing.The experimental results show that the sparse representation method based on wavelet transform and LASSO achieves higher compression ratio in speech compression coding,providing reliable technical support for speech communication and storage.
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