Multimodal Emotion Recognition

This is a leaderboard for multimodal emotion recognition on the IEMOCAP dataset. The modality abbreviations are A: Acoustic T: Text V: Visual

Please include the modality in the bracket after the model name.

All models must use standard five emotion categories and are evaluated in standard leave-one-session-out (LOSO). See the papers for references.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 121–130 of 180 papers

Title	Date	Tasks	Status	Hype
Bias and Fairness on Multimodal Emotion Detection Algorithms	May 11, 2022	Emotion RecognitionFairness	—Unverified	0
COGMEN: COntextualized GNN based Multimodal Emotion recognitioN	May 5, 2022	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1
MMER: Multimodal Multi-task Learning for Speech Emotion Recognition	Mar 31, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1
A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition	Mar 28, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1
Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition	Mar 24, 2022	Arousal EstimationEmotion Recognition	—Unverified	0
Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responses	Feb 19, 2022	DescriptiveEmotion Recognition	CodeCode Available	1
Multimodal Emotion Recognition using Transfer Learning from Speaker Recognition and BERT-based models	Feb 16, 2022	Data AugmentationEmotional Intelligence	—Unverified	0
Interpretability for Multimodal Emotion Recognition using Concept Activation Vectors	Feb 2, 2022	Decision MakingEmotion Recognition	—Unverified	0
Group Gated Fusion on Attention-based Bidirectional Alignment for Multimodal Emotion Recognition	Jan 17, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1
A proposal for Multimodal Emotion Recognition using aural transformers and Action Units on RAVDESS dataset	Dec 30, 2021	Autonomous DrivingEmotion Recognition	CodeCode Available	1

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All datasets IEMOCAP-4 MELD IEMOCAP CMU-MOSEI-Sentiment CMU-MOSEI-Sentiment-3 Expressive hands and faces dataset (EHF).MELD-Sentiment

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	86.52	—	Unverified
2	Joyful	Weighted F1	85.7	—	Unverified
3	COGMEN	Weighted F1	84.5	—	Unverified
4	DANN	Accuracy	82.7	—	Unverified
5	MMER	Accuracy	81.7	—	Unverified
6	PATHOSnet v2	Accuracy	80.4	—	Unverified
7	Self-attention weight correction (A+T)	Accuracy	76.8	—	Unverified
8	CHFusion	Accuracy	76.5	—	Unverified
9	bc-LSTM	Weighted F1	74.1	—	Unverified
10	Audio + Text (Stage III)	F1	70.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	66.71	—	Unverified
2	Audio + Text (Stage III)	Weighted F1	65.8	—	Unverified
3	Joyful	Weighted F1	61.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	72.81	—	Unverified
2	Joyful	Weighted F1	70.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	44.93	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	66.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SMPLify-X	v2v error	52.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GraphSmile	Weighted F1	74.31	—	Unverified