摘要
主要介绍基于HHT变换提取的瞬时能量(A)和瞬时频率(f)的标准差参数作为病态嗓音特征参数的有效性,详细描述了A-f新特征参数的提取过程,并利用DHMM模型对A-f标准差新特征参数,与语音识别中常用的MFCC系数进行识别。识别结果表明,由HHT变换提取的A-f标准差参数更适合于描述病态嗓音,更能有效区分病态嗓音和正常嗓音。
This paper mainly proposes the validity of instantaneous energy＇s and instantaneous frequency＇s standard deviation parameter used as the pathological voice＇s characteristics extracted based on HHT,describs the process of extracting characteris- tics in detail,and recognizes the new characteristic parameter and the MFCC coefficient uses the DHMM model.The result from recognition shows that,A-f standard deviation parameter which based on HHT is more resultful to use on describing pathological voice,distinguish the pathological voice from normal voice more effectively.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第34期217-219,245,共4页
Computer Engineering and Applications
基金
广西省自然科学基金(the Natural Science Foundation of Guangxi Province of China under Grant No.0448035)。
关键词
希尔伯特黄变换
病态嗓音
A—f标准差参数
离散隐含马尔可夫模型
MEL频率倒谱系数
Hilbert-Huang Transform（HHT）
pathological voice
A-f standard deviation parameter
Discrete Hidden Markov Models（DHMM）
Mel Frequency Cepstrum Coefficient（MFCC）
