| 基于Bessel函数展开的ICA语音增强 |
| |
| 引用本文： | 熊志伟,全海燕,周荣强. 基于Bessel函数展开的ICA语音增强[J]. 计算机工程, 2013, 39(3): 311-315 |
| |
| 作者姓名： | 熊志伟 全海燕 周荣强 |
| |
| 作者单位： | 昆明理工大学信息工程与自动化学院,昆明,650093 |
| |
| 基金项目： | 云南省自然科学基金资助项目(2009ZC048M) |
| |
| 摘 要： | 将源信号的先验知识以参考信号的形式引入到独立分量分析(ICA)学习算法中，从混合信号中仅提取期望的源信号。依据语音信号传播机理和Bessel函数展开系数对语音信号的表征能力，给出基于Bessel函数展开的参考信号构建方法，从混合语音信号中提取出期望的语音信号。仿真和性能分析结果表明，该方法能在噪声干扰的情况下达到语音增强的目的。
|
| 关 键 词： | 盲源分离 独立分量分析 参考独立分量分析 Bessel函数 经验模式分解 语音增强 |
| 收稿时间： | 2012-03-27 |
Independent Component Analysis Voice Enhancement Based on Bessel Function Expansion |
| |
| XIONG Zhi-wei , QUAN Hai-yan , ZHOU Rong-qiang. Independent Component Analysis Voice Enhancement Based on Bessel Function Expansion[J]. Computer Engineering, 2013, 39(3): 311-315 |
| |
| Authors: | XIONG Zhi-wei QUAN Hai-yan ZHOU Rong-qiang |
| |
| Affiliation: | (Institute of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650093, China) |
| |
| Abstract: | Independent Component Analysis with Reference(ICA-R) can extract only desired source signal from mixtures of all source signals by incorporating prior information into the learning algorithm as reference signal. The rule of voice signal transmission and Bessel function expansion can describe voice signals. This paper applies Independent Component Analysis with Reference(ICA-R) to extract a target voice signal from mixtures of all source signals by constructing a proper reference signal with Bessel function expansion, computer simulation results and performance analysis demonstrate the method can get better voice enhancement effect under noise interference situation. |
| |
| Keywords: | Blind Source Separation(BSS) Independent Component Analysis(ICA) ICA with Reference(ICA-R) Bessel function Empirical Mode Decomposition(EMD) voice enhancement |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程》浏览原始摘要信息 |
|
点击此处可从《计算机工程》下载全文 |
