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Recognition of emotions in speech by a hierarchical approach
2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, 2009This paper deals with speech emotion analysis within the context of increasing awareness of the wide application potential of affective computing. Unlike most works in the literature which mainly rely on classical frequency and energy based features along with a single global classifier for emotion recognition, we propose in this paper some new ...
Xiao, Zhongzhe +3 more
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Intermediary Fuzzification in Speech Emotion Recognition
2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2020Affective systems are getting increasingly more attention from researchers and high-tech companies in order to enable the acknowledgment or adaptation to a user’s mood. Emotion classification is typically a hard problem due to the number of subtle cues which are present in human facial and body expressions, or in voiced utterances.
Gustavo Assunção, Paulo Menezes 0001
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Transfer Learning for Speech Emotion Recognition
2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), 2019Speech emotion recognition is still challenging due to the complexity of emotion. Most of the current research is based on the enough data, and the training data and test data are from the same corpus. Obviously, this is not in line with the actual application scene. In addition, the emotion annotation of large amounts speech data is also a challenging
Zhijie Han 0001 +2 more
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Multiroom Speech Emotion Recognition
2022 30th European Signal Processing Conference (EUSIPCO), 2022Erez Shalev, Israel Cohen
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Evaluation of emotion recognition from speech
2012 20th Signal Processing and Communications Applications Conference (SIU), 2012Over the last few years, interest on paralinguistic information classification has grown considerably. However, in comparison to related speech processing tasks such as Automatic Speech and Speaker Recognition, practically no standardised corpora and test-conditions exist to compare performances under exactly the same conditions.
Elif Bozkurt, Engin Erzin
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NMF features for speech emotion recognition
Proceedings of the 2009 International Conference on Hybrid Information Technology, 2009There are numerous algorithms to detect emotion from speech signals. Among the algorithms, we selected spectral analysis and fused Non-negative Matrix Factorization (NMF) for obvios emotion classification. The algorithm has been tested in several different ways by varying NMF and the speech database. The experimental results show performance of 90% and
Kyungjoong Jeong +2 more
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Emotion Prompting for Speech Emotion Recognition
INTERSPEECH 2023, 2023Xingfa Zhou +5 more
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2015
Recent years have been marked by a growing need for systems that can grasp human emotions and in particular, recognize emotions. Emotions lie at the centre of any social communication and form the basis for an intelligent and meaningful interaction. The chapter further discusses the acoustic correlates of emotions and describes various techniques and ...
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Recent years have been marked by a growing need for systems that can grasp human emotions and in particular, recognize emotions. Emotions lie at the centre of any social communication and form the basis for an intelligent and meaningful interaction. The chapter further discusses the acoustic correlates of emotions and describes various techniques and ...
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Speech Emotion Recognition Using CNN
Proceedings of the 22nd ACM international conference on Multimedia, 2014Deep learning systems, such as Convolutional Neural Networks (CNNs), can infer a hierarchical representation of input data that facilitates categorization. In this paper, we propose to learn affect-salient features for Speech Emotion Recognition (SER) using semi-CNN. The training of semi-CNN has two stages.
Zhengwei Huang +3 more
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Emotion Recognition and Conversion for Mandarin Speech
2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009In this study, some research activities on expressive speech recognition and conversion will be introduced. A database consisting of five kinds of speech emotions (i.e. happiness, sadness, surprise, anger and neutral) is used. Not only those traditional features such as mfcc, plp, and pitch are studied, but also a new feature extraction method based on
Yu Zhou +3 more
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