Multimodal Emotion Detection via Attention-Based Fusion of Extracted Facial and Speech Features

Methods for detecting emotions that employ many modalities at the same time have been found to be more accurate and resilient than those that rely on a single sense. This is due to the fact that sentiments may be conveyed in a wide range of modalities, each of which offers a different and complement...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 23; no. 12; p. 5475
Main Authors:	Mamieva, Dilnoza, Abdusalomov, Akmalbek Bobomirzaevich, Kutlimuratov, Alpamis, Muminov, Bahodir, Whangbo, Taeg Keun
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 09.06.2023 MDPI
Subjects:	Accuracy attention mechanism CNN Datasets Deep learning Emotions Facial Expression facial feature Humans Identification systems multimodal emotion recognition Neural networks Recognition, Psychology Signal processing Speech speech feature speech feature CNN facial feature attention mechanism multimodal emotion recognition
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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