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 161–170 of 180 papers

Title	Date	Tasks	Status	Hype
Multimodal Emotion Recognition Using Deep Canonical Correlation Analysis	Aug 13, 2019	Binary ClassificationEmotion Recognition	CodeCode Available	0
Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment Analysis	Apr 17, 2019	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	0
Multimodal Speech Emotion Recognition and Ambiguity Resolution	Apr 12, 2019	BIG-bench Machine LearningEmotion Recognition	CodeCode Available	0
MULTI-MODAL EMOTION RECOGNITION ON IEMOCAP WITH NEURAL NETWORKS.	Nov 12, 2018	Emotion RecognitionMultimodal Emotion Recognition	—Unverified	0
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations	Nov 1, 2018	Emotion ClassificationEmotion Recognition in Conversation	CodeCode Available	1
Multimodal Speech Emotion Recognition Using Audio and Text	Oct 10, 2018	Emotion ClassificationEmotion Recognition	CodeCode Available	0
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection	Oct 1, 2018	Emotion RecognitionEmotion Recognition in Conversation	—Unverified	0
Music Mood Detection Based On Audio And Lyrics With Deep Neural Net	Sep 19, 2018	Multimodal Emotion RecognitionMusic Emotion Recognition	CodeCode Available	1
Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion Recognition	Sep 13, 2018	Emotion ClassificationEmotion Recognition	CodeCode Available	0
Multimodal Sentiment Analysis using Hierarchical Fusion with Context Modeling	Jun 16, 2018	Multimodal Emotion RecognitionMultimodal Sentiment Analysis	CodeCode Available	0

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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