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 61–70 of 180 papers

Title	Date	Tasks	Status	Score
Multimodal Emotion Recognition Using Deep Canonical Correlation Analysis	Aug 13, 2019	Binary ClassificationEmotion Recognition	CodeCode Available	5
Multimodal Speech Emotion Recognition and Ambiguity Resolution	Apr 12, 2019	BIG-bench Machine LearningEmotion Recognition	CodeCode Available	5
Multi-level Fusion of Wav2vec 2.0 and BERT for Multimodal Emotion Recognition	Jul 11, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	5
Multimodal Behavioral Markers Exploring Suicidal Intent in Social Media Videos	Oct 1, 2019	Multimodal Emotion RecognitionMultimodal Sentiment Analysis	CodeCode Available	5
Modality-Collaborative Transformer with Hybrid Feature Reconstruction for Robust Emotion Recognition	Dec 26, 2023	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	5
Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep Learning	Apr 16, 2018	Deep LearningEmotion Recognition	CodeCode Available	5
Leveraging Contrastive Learning and Self-Training for Multimodal Emotion Recognition with Limited Labeled Samples	Aug 23, 2024	Contrastive LearningEmotion Recognition	CodeCode Available	5
Learning Noise-Robust Joint Representation for Multimodal Emotion Recognition under Incomplete Data Scenarios	Sep 21, 2023	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	5
Learning Alignment for Multimodal Emotion Recognition from Speech	Sep 6, 2019	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	5
Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment Analysis	Apr 17, 2019	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	5

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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