语音信号的量子随机滤波降噪方法

• 作 者: 赖联有 金福江 吴浩瀚
• 机 构: 华侨大学机电及自动化学院,集美大学信息工程学院,华侨大学信息科学与工程学院,
• 出 处: 信息与控制
• 发表日期: 2015年05期
• 关键词: speech de-noising speech enhancement quantum stochastic filter Schr(o)dinger equ

针对传统语音滤波降噪算法适应性差,一种算法难以对多种不同类型的噪声同时有效的问题,提出量子随机滤波自适应学习算法.该算法适应性强,可以对含有各种不同类型噪声的语音信号进行有效的滤波降噪,能很好地解决传统语音滤波算法适应性差的问题.实验结果证明了该算法的有效性.

Aiming at the poor adaptability of the traditional speech filtering denoising algorithm and an algorithm which is difficult to effectively treat many different types of noise at the same time, a quantum random filtering adaptive learning algorithm is proposed. The algorithm has strong adaptability and can be applied to noise reduction with different types of noise Speech signal to effectively filter noise reduction, can well solve the problem of poor adaptability of traditional speech filtering algorithm.The experimental results show the effectiveness of the algorithm.