摘要
通过分析含噪语音信号的特点,引入能够兼顾人耳听觉特性的听觉感知小波变换,构造了新的小波阈值函数,并对小波变换分解后的阈值进行基于微粒群算法的分层优化.仿真实验表明,该方法在不同信噪比条件下均具有较好的去噪性能,语音的可懂度和听觉效果得到有效提高.
By analyzing the characteristic of noisy speech signals,audio perception wavelet transform was introduced,which considered human auditory effect.New wavelet threshold function was constructed and hierarchical optimization was performed based on particle swarm optimization algorithm after wavelet transform.Simulation indicated that the proposed method had a good de-noising effect under circumstances of different signal-noise-ratio(SNR),improved speech intelligibility and auditory effect.
出处
《湖南文理学院学报(自然科学版)》
CAS
2014年第2期35-39,共5页
Journal of Hunan University of Arts and Science(Science and Technology)
基金
湖南省科技计划资助项目(2010SK3052)
光电信息集成与光学制造技术湖南省重点实验室资助项目
湖南文理学院重点学科建设项目(无线电物理)
关键词
语音去噪
听觉感知小波变换
分层阈值
微粒群算法
speech de-noising
auditory perception wavelet transform
Hierarchical threshold
particle swarm optimization