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Fusing facial and speech cues for enhanced multimodal emotion recognition · Study

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ArticleFusing facial and speech cues for enhanced multimodal emotion recognition

Pragya Singh Tomar2024

Article2024

Fusing facial and speech cues for enhanced multimodal emotion recognition

Pragya Singh Tomar · Kirti Mathur · Ugrasen Suman

40 citations·0/0 files stored·International Journal of Information Technology

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Emotion and Mood Recognition Speech and Audio Processing Sentiment Analysis and Opinion Mining

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References

2017A review of affective computing: From unimodal analysis to multimodal fusion 2004Analysis of emotion recognition using facial expressions, speech and multimodal information 2017Automatic speech emotion recognition using recurrent neural networks with local attention 2020Speech emotion recognition with deep convolutional neural networks 2006The eNTERFACE’05 Audio-Visual Emotion Database 2017Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching 2013Deep learning for robust feature generation in audiovisual emotion recognition 2017Learning Affective Features With a Hybrid Deep Model for Audio–Visual Emotion Recognition

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2021Information Fusion in Attention Networks Using Adaptive and Multi-Level Factorized Bilinear Pooling for Audio-Visual Emotion Recognitionarticle · 7 shared references 2019Deep Learning for Human Affect Recognition: Insights and New Developmentsarticle · 6 shared references 2019A snapshot research and implementation of multimodal information fusion for data-driven emotion recognitionarticle · 5 shared references 2023A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methodsarticle · 5 shared references 2017Deep Spatio-Temporal Features for Multimodal Emotion Recognitionother · 5 shared references 2020Learning Better Representations for Audio-Visual Emotion Recognition with Common Informationarticle · 5 shared references

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Year2024

Typearticle

Published2024-01-24

VenueInternational Journal of Information Technology

ISSN-L2511-2104

Languageen

Citations40

Files0 public / 0

ShelfEmotion and Mood Recognition

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doi10.1007/s41870-023-01697-7

openalex_workW4391167693

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