| 谢珊,曾以成,蒋阳波.希尔伯特边际谱在语音情感识别中的应用[J].声学技术,2009,(2):148~152 |
| 希尔伯特边际谱在语音情感识别中的应用 |
| Application of Hilbert marginal spectrum in speech emotion recognition |
| 投稿时间：2008-03-01 修订日期：2008-04-13 |
| DOI： |
| 中文关键词: 情感识别 边际谱 HHT |
| 英文关键词: emotion recognition marginal spectrum HHT |
| 基金项目: |
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| 摘要点击次数: 1514 |
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| 中文摘要: |
| 利用希尔伯特-黄变换(Hilbert-Huang Transform,HHT)对情感语音进行处理,得到其边际谱,然后对比分析四种情感即高兴、生气、厌恶、无情感语音信号边际谱的特征,提出四个特征量:子带能量(SE)、子带能量的一阶差分(DSE)、子带能量倒谱系数(SECC)、子带能量倒谱系数的一阶差分(DSECC)用于情感识别。用它们作说话人无关,文本无关的语音情感识别,得到最高90%的识别率,比基于傅立叶变换的梅尔频率倒谱系数(MFCC)高22个百分点。实验结果表明,基于HHT边际谱的特征能够较好地反映语音信号中的情感信息。 |
| 英文摘要: |
| Marginal spectrum of the emotional speech is obtained through Hilbert-Huang Transform.Speech signals of four different emotions,namely happy,angry,boring and natrual,are analyzed contrastively focusing on the characteristics of the marginal spectrum.Then four features:SE,DSE,SECC and DSECC are extracted for emotion recognition.Finally speaker-independent and text-independent emotion recognitions are simulated by using these features respectively,which gains the best recognition rate of 90%,which is 22 percentage higher than Fourier Transform based feature MFCC.Thus,conclusion is drawn that HHT marginal spectrum can well reflect the emotional information in speech. |
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