改进的正交匹配追踪的语音增强算法

Speech enhancement algorithm based on improved orthogonal matching pursuit

为了提高传统正交匹配追踪算法的语音增强性能和运算速度,该研究基于稀疏编码理论,提出了一种改进的正交匹配追踪算法的语音增强算法。其一,将K-奇异值分解算法与正交匹配追踪算法相结合,通过设置能量阈值的方法,提高正交匹配追踪算法的语音增强性能;其二,通过改进传统正交匹配追踪算法中信号稀疏逼近的计算方法,提高算法的运算速度。结果表明,改进的正交匹配追踪算法的语音增强算法与传统K-奇异值分解语音增强算法相比,在短时客观可懂度的值基本保持不变的情况下,语音质量客观评估值提高10.84%,取得了更好的增强效果;改进的正交匹配追踪算法的运算速度与传统正交匹配追踪算法相比提高近一倍。

In order to enhance the performance of the speech enhancement and the running speed of traditional orthogonal matching pursuit(OMP)algorithm,based on sparse coding theory,this paper proposes an improved speech enhancement algorithm for OMP algorithm.Firstly,combining K-singular value decomposition(K-SVD)algorithm with OMP algorithm,we set up the energy threshold to improve the speech enhancement performance of OMP algorithm.Secondly,we increase the algorithm speed by improving the traditional calculation method of signal sparse approximation in OMP algorithm.The results show that compared with the traditional KSVD algorithm,the perceptual evaluation of speech quality(PESQ)of the improved OMP algorithm increases by 10.84%while the value of short-time objective intelligibility(STOI)remains essentially unchanged.This algorithm has achieved better results.The computational speed of the improved OMP algorithm is nearly twice as high as that of the traditional OMP algorithm.