摘要
针对单通道语音增强问题,基于计算听觉场景分析(CASA)的原理,提出了一种基于CASA计算模型的语音增强改进算法。该算法在特征提取中选择了目标语音有效能量、信道互相关等特征,对语谱能量和互相关特征的阈值选取进行了改进。在5种低信噪比噪声干扰条件下的仿真实验结果证明,该算法输出增强语音的信噪比平均提高了9.32dB,有效地抑制了噪声。
Based on computational auditory scene analysis (CASA), this paper proposes an improved algorithm for monaural speech enhancement. In the proposed algorithm, both effective energy of target speech and cross-channel correlation are chosen as extracted feature. Moreover, this algorithm improves the threshold selection on energy spectrum and cross-channel correlation feature. Under the condition of low SNR with 5 different noises, the experimental results show that the proposed algorithm can raise the output SNR by 9.32 dB averagely, and attenuates noise effectively.
出处
《华东理工大学学报(自然科学版)》
CAS
CSCD
北大核心
2012年第5期617-621,共5页
Journal of East China University of Science and Technology
关键词
语音增强
计算听觉场景分析
语音有效能量
信道互相关
二值掩码
speech enhancement
computational auditory scene analysis
effective energy of targetspeech
cross channel correlation
binary mask