Automatic Recognition of Emotions from Speech
نویسندگان
چکیده
منابع مشابه
Automatic Recognition of Emotions from the Acoustic Speech Signal
This research aims at investigating several feature sets such as acoustic, lexical, and discourse features, and classification algorithms for classifying spoken utterances based on the emotional state of the speaker [1]. Besides applications in enabling natural human machine interfaces, the problem motivates development of novel classification algorithms that can operate with sparse data. Anoth...
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This paper investigates the effects of standard speech compression techniques on the accuracy of automatic emotion recognition. Effects of Adaptive Multi-Rates (AMR), Adaptive Multi-Rate Wideband (AMR-WB) and Extended Adaptive Multi-Rate Wideband (AMR-WB+) speech codecs were compared against emotion recognition from uncompressed speech. The recognition methods included techniques based on three...
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In this article we give guidelines on how to address the major technical challenges of automatic emotion recognition from speech in human-computer interfaces, which include audio segmentation to find appropriate units for emotions, extraction of emotion relevant features, classification of emotions, and training databases with emotional speech. Research so far has mostly dealt with offline eval...
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The interest in emotion recognition from speech has increased in the last decade. Emotion recognition can improve the quality of services and the quality of life of people. One of the main problems in emotion recognition from speech is to find suitable features to represent the phenomenon. This paper proposes new features based on the energy content of wavelet based time-frequency (TF) represen...
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ژورنال
عنوان ژورنال: International Journal of Computational Linguistics Research
سال: 2019
ISSN: 0976-416X,0976-4178
DOI: 10.6025/jcl/2019/10/4/101-107