Results 1 to 10 of about 15,656 (256)
A Methodical Framework Utilizing Transforms and Biomimetic Intelligence-Based Optimization with Machine Learning for Speech Emotion Recognition. [PDF]
Biomimetics (Basel)Prabhakar SK, Won DO.
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Cochleogram-Based Speech Emotion Recognition with the Cascade of Asymmetric Resonators with Fast-Acting Compression Using Time-Distributed Convolutional Long Short-Term Memory and Support Vector Machines. [PDF]
Biomimetics (Basel)Parlak C.
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Selective Acoustic Feature Enhancement for Speech Emotion Recognition With Noisy Speech. [PDF]
IEEE/ACM Trans Audio Speech Lang ProcessLeem SG +4 more
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Emotion recognition from speech: a review
International Journal of Speech Technology, 2012Emotion recognition from speech has emerged as an important research area in the recent past. In this regard, review of existing work on emotional speech processing is useful for carrying out further research. In this paper, the recent literature on speech emotion recognition has been presented considering the issues related to emotional speech corpora,
Shashidhar Koolagudi +2 more
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Italian Speech Emotion Recognition
2023 24th International Conference on Digital Signal Processing (DSP), 2023Affective computing is gaining increased interest by the scientific community in the last decades with the acoustic modality playing a central role. This paper presents an extensive computational analysis of emotional speech focusing on the Italian language.
Mantegazza, Irene, Ntalampiras, Stavros
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2014 International Conference on Advances in Electronics Computers and Communications, 2014
In the past decade a lot of research has gone into Automatic Speech Emotion Recognition(SER). The primary objective of SER is to improve man-machine interface. It can also be used to monitor the psycho physiological state of a person in lie detectors. In recent time, speech emotion recognition also find its applications in medicine and forensics.
S. Lalitha +3 more
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In the past decade a lot of research has gone into Automatic Speech Emotion Recognition(SER). The primary objective of SER is to improve man-machine interface. It can also be used to monitor the psycho physiological state of a person in lie detectors. In recent time, speech emotion recognition also find its applications in medicine and forensics.
S. Lalitha +3 more
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Application of Emotion Recognition and Modification for Emotional Telugu Speech Recognition
Mobile Networks and Applications, 2018Majority of the automatic speech recognition systems (ASR) are trained with neutral speech and the performance of these systems are affected due to the presence of emotional content in the speech. The recognition of these emotions in human speech is considered to be the crucial aspect of human-machine interaction.
Vishnu Vidyadhara Raju Vegesna +2 more
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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 ...
Zhongzhe Xiao +3 more
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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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