自动化与仪表2024,Vol.39Issue(9) :131-137.DOI:10.19557/j.cnki.1001-9944.2024.09.030

BDO与VMD-EAM算法融合的单通道语音增强模型

Single-channel Speech Enhancement Model Based on BDO and VMD-EAM Al-gorithms

王洪涛 毛露露
自动化与仪表2024,Vol.39Issue(9) :131-137.DOI:10.19557/j.cnki.1001-9944.2024.09.030

BDO与VMD-EAM算法融合的单通道语音增强模型

Single-channel Speech Enhancement Model Based on BDO and VMD-EAM Al-gorithms

王洪涛 1毛露露2
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作者信息

  • 1. 咸阳师范学院 外国语学院,咸阳 712000;咸阳师范学院 实验实训中心,咸阳 712000
  • 2. 咸阳师范学院 实验实训中心,咸阳 712000
  • 折叠

摘要

为了改善VMD在单通道语音增强中关键参数选择难、声学特征缺失多的问题,该文提出了一种BDO与VMD-EAM算法融合的单通道语音增强模型.利用DBO对输入的含噪音频进行处理,得到分解模态数与惩罚因子的最佳组合,实现VMD在分解中关键参数的自适应寻优,再根据EAM的相似度评估结果完成IMF分量的分类,对噪声分量的高频信息使用小波阈值法进行滤除,最后基于IVMD-EAM模型的重构原理实现信号重构.仿真验证及实测实验表明,所构建的语音增强模型可有效抑制噪声并提升英文语音的增强效果,各项性能评价指标也显著优于其他2种单通道语音增强模型.

Abstract

In order to improve the problem that it is difficult to select the key parameters of VMD and the lack of acoustic features in single-channel speech enhancement,a single-channel speech enhancement model based on BDO and VMD-EAM algorithm is proposed.Firstly,the DBO is used to process the input noisy speech to obtain the opti-mal combination of the number of decomposition modes and penalty factor,so that the adaptive optimization of the key parameters of VMD is realized.Then,the classification of IMF component is completed according to the similari-ty evaluation results of EAM,and the high-frequency information of noise component is filtered by wavelet threshold method.Finally,the signal was reconstructed based on the reconstruction principle of IVMD-EAM model.Simulation and real experiments show that the proposed speech enhancement model can effectively suppress noise and improve the enhancement effect of English speech,and all performance evaluation indicators are significantly better than the other two single-channel speech enhancement models.

关键词

语音增强/单通道/BDO/VMD-EAM算法/信号重构

Key words

speech enhancement/single-channel/BDO/VMD-EAM algorithm/signal reconstruction

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基金项目

咸阳师范学院科研计划重点项目(XSYK21030)

出版年

2024
自动化与仪表
天津市工业自动化仪表研究所 天津市自动化学会

自动化与仪表

CSTPCD
影响因子:0.548
ISSN:1001-9944
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