| 基于基频特征的情感语音识别研究* |
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| 引用本文： | 郭鹏娟,蒋冬梅,Hichem Sahli,Werner Verhelst.基于基频特征的情感语音识别研究*[J].计算机应用研究,2007,24(10):101-103. |
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| 作者姓名： | 郭鹏娟 蒋冬梅 Hichem Sahli Werner Verhelst |
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| 作者单位： | 1. 西北工业大学,计算机学院,西安,710072
2. 比利时布鲁塞尔自由大学,电子与信息工程系,比利时 |
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| 摘 要： | 探索在不同的情感状态下的基音特征变化规律.通过对含有生气、高兴、悲伤情感语音信号进行分析,总结了情感语音基频的变化规律,确定了用于情感识别的12维的基频的基本特征以及扩展特征,运用混合高斯模型进行情感识别,并作了识别实验,获得了较好的结果.
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| 关 键 词： | 语音信号 基频 情感特征 情感识别 基频特征 情感识别 语音识别 研究 pitch based speech recognition 结果 实验 高斯模型 混合 运用 扩展特征 基本特征 情感语音信号 分析 变化规律 基音 情感状态 |
| 文章编号： | 1001-3695（2007）10-0101-03 |
| 修稿时间： | 2006-07-04 |
Research on emotional speech recognition based on pitch |
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| GUO Peng juan,JIANG Dong mei,Hichem Sahli,Werner Verhelst.Research on emotional speech recognition based on pitch[J].Application Research of Computers,2007,24(10):101-103. |
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| Authors: | GUO Peng juan JIANG Dong mei Hichem Sahli Werner Verhelst |
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| Abstract: | This paper first analyzed the change of pitch in speech signal under four emotions such as angry, happy, neutral and sad. Then twelve pitch related emotional features were extracted and used to train the Gaussian mixture models (GMMs) for each emotional state. In emotion recognition, the emotional state with the GMM having the maximal likelihood ratio was determined as the final out. The experimental result shows that the pitch related features and GMM are effective in emotion recognition from speech. |
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| Keywords: | speech signal pitch emotional feature emotion recognition |
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