Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/1445
Title: Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers
Authors: Akcay, Mehmet Berkehan
Oguz, Kaya
Keywords: Speech emotion recognition
Survey
Speech features
Classification
Speech databases
Voice Quality
Communicating Emotion
Spectral Features
Neural-Networks
Classification
Valence
Expression
Arousal
Adversarial
Audio
Publisher: Elsevier
Abstract: Speech is the most natural way of expressing ourselves as humans. It is only natural then to extend this communication medium to computer applications. We define speech emotion recognition (SER) systems as a collection of methodologies that process and classify speech signals to detect the embedded emotions. SER is not a new field, it has been around for over two decades, and has regained attention thanks to the recent advancements. These novel studies make use of the advances in all fields of computing and technology, making it necessary to have an update on the current methodologies and techniques that make SER possible. We have identified and discussed distinct areas of SER, provided a detailed survey of current literature of each, and also listed the current challenges.
URI: https://doi.org/10.1016/j.specom.2019.12.001
https://hdl.handle.net/20.500.14365/1445
ISSN: 0167-6393
1872-7182
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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