情绪识别和情绪识别改进使用共振体相关特征

Q4 Engineering

Majlesi Journal of Electrical Engineering Pub Date : 2010-09-22 DOI:10.1234/MJEE.V4I4.266

D. Gharavian, M. Sheikhan

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引用次数: 6

摘要

情感在人机交流的自然度中起着重要的作用。因此，近几十年来，许多研究人员对语音的计算机化情感识别进行了研究。本文研究了共振峰相关特征对提高情绪检测系统性能的影响。为此，将前三个共振峰的各种形式和组合连接到一个流行的特征向量上，并使用高斯混合模型作为分类器。实验结果表明，在四种情绪状态下，平均识别率为69%，仅在特征向量中加入一个共振峰相关参数，性能有明显提高。在此基础上，提出了混合情感识别/识别的体系结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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EMOTION RECOGNITION AND EMOTION SPOTTING IMPROVEMENT USING FORMANT-RELATED FEATURES

Emotion has an important role in naturalness of man-machine communication. So, computerized emotion recognition from speech is investigated by many researchers in the recent decades. In this paper, the effect of formant-related features on improving the performance of emotion detection systems is experimented. To do this, various forms and combinations of the first three formants are concatenated to a popular feature vector and Gaussian mixture models are used as classifiers. Experimental results show average recognition rate of 69% in four emotional states and noticeable performance improvement by adding only one formant-related parameter to feature vector. The architecture of hybrid emotion recognition/spotting is also proposed based on the developed models.

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来源期刊

Majlesi Journal of Electrical Engineering Engineering-Electrical and Electronic Engineering

CiteScore

1.20

自引率

0.00%

发文量

期刊介绍： The scope of Majlesi Journal of Electrcial Engineering (MJEE) is ranging from mathematical foundation to practical engineering design in all areas of electrical engineering. The editorial board is international and original unpublished papers are welcome from throughout the world. The journal is devoted primarily to research papers, but very high quality survey and tutorial papers are also published. There is no publication charge for the authors.