摘要
针对传统谱减算法在低信噪比情况下的性能不佳的问题,提出了一种基于Katz维数的改进谱减算法,利用一种新的动态调整过减因子α的策略实现对谱减法的改进,提升了算法性能.实验结果表明,相比于传统谱减法、小波变换法及谱减结合小波变换的语音增强法,所提算法在信噪比、主观感知质量和可懂度三个方面都得到了提升.
The performance of traditional spectral subtraction algorithms is often unsatisfactory in the case of low signalto-noise ratio conditions.To solve this problem,an improved spectral subtraction algorithm based on the Katz dimension is proposed.Furthermore,a new strategy involving the dynamic adjustment of over-subtraction factorαis used to improve spectral subtraction,which improves the algorithm′s performance.Experimental results show that compared with the traditional spectral subtraction,wavelet transform,and spectral subtraction combined with wavelet transform speech enhancement method,the proposed algorithm improve the results in three aspects:signal-to-noise ratio,perceptual evaluation of speech quality,and short-time objective intelligibility.
作者
刘炜杰
安桐
张涛
LIU Weijie;AN Tong;ZHANG Tao(School of Electrical and Information Engineering,Tianjin University,Tianjin 300072,China;Jiangsu Zhongqi Environmental Technology Co.,Ltd,Nantong 226000,China)
出处
《信息与控制》
CSCD
北大核心
2021年第6期677-684,共8页
Information and Control
关键词
语音增强
分形维数
谱减法
Katz方法
speech enhancement
fractal dimension
spectral subtraction
Katz method
