计算机科学 ›› 2011, Vol. 38 ›› Issue (Z10): 434-436.

• 新技术应用 • 上一篇    下一篇

基于EMD的语音特征信息提取

王辉,李生华   

  1. (贺州学院物理与电子信息工程系 贺州542800)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Feature Extraction of Speech Signal Based on Empirical Mode Decomposition

WANG Hui,Li Sheng-hua   

  • Online:2018-11-16 Published:2018-11-16

摘要: 有效提取语音信号的特征信息是语音识别的关键。对语音信号采用经验模态分解法可得到语音的一系列本征模函数,提取本征模函数的过程是降低语音信号冗余度的过程。在语音识别的试验中以本征模函数为训练模型较传统的识别方法识别率更高。仿真结果表明:方法是有效的,用于提取语音的特征信息是可行的。

关键词: 语音信号,经验模态分解,特征信息,语音识别,本征模函数

Abstract: Effectively extracting feature information of speech signal is the key of speech recognition. By empirical mode decomposition method, a series of intrinsic mode function can be got.Extraction process of intrinsic mode function is to reduce its redundancy. Experimental results show that the empirical mode decomposition method can decrease the recognition error rate. EMD is an effective method. It is feasible to extract the feature from speech signals with EMD.

Key words: Speech signal, EMD, Feature information, Speech recognition, Intrinsic mode function

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