SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–175 of 180 papers

TitleStatusHype
Combining deep and unsupervised features for multilingual speech emotion recognitionCode0
Context-Dependent Domain Adversarial Neural Network for Multimodal Emotion Recognition—0
Emotion recognition by fusing time synchronous and time asynchronous representations—0
An Audio-Video Deep and Transfer Learning Framework for Multimodal Emotion Recognition in the wild—0
Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition—0
EmotiCon: Context-Aware Multimodal Emotion Recognition using Frege's Principle—0
Attentive Modality Hopping Mechanism for Speech Emotion RecognitionCode0
Multimodal Affective States Recognition Based on Multiscale CNNs and Biologically Inspired Decision Fusion Model—0
M3ER: Multiplicative Multimodal Emotion Recognition Using Facial, Textual, and Speech Cues—0
Multimodal Behavioral Markers Exploring Suicidal Intent in Social Media VideosCode0
Learning Alignment for Multimodal Emotion Recognition from SpeechCode0
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning—0
Multimodal Emotion Recognition Using Deep Canonical Correlation AnalysisCode0
Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment AnalysisCode0
Multimodal Speech Emotion Recognition and Ambiguity ResolutionCode0
MULTI-MODAL EMOTION RECOGNITION ON IEMOCAP WITH NEURAL NETWORKS.—0
Multimodal Speech Emotion Recognition Using Audio and TextCode0
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection—0
Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion RecognitionCode0
Multimodal Sentiment Analysis using Hierarchical Fusion with Context ModelingCode0
Context-aware Cascade Attention-based RNN for Video Emotion Recognition—0
Convolutional Attention Networks for Multimodal Emotion Recognition from Speech and Text Data—0
Multimodal Emotion Recognition for One-Minute-Gradual Emotion Challenge—0
Framewise approach in multimodal emotion recognition in OMG challenge—0
Contextual Dependencies in Time-Continuous Multidimensional Affect Recognition—0
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All datasetsIEMOCAP-4MELDIEMOCAPCMU-MOSEI-SentimentCMU-MOSEI-Sentiment-3Expressive hands and faces dataset (EHF).MELD-Sentiment

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F186.52—Unverified
2JoyfulWeighted F185.7—Unverified
3COGMENWeighted F184.5—Unverified
4DANNAccuracy82.7—Unverified
5MMERAccuracy81.7—Unverified
6PATHOSnet v2Accuracy80.4—Unverified
7Self-attention weight correction (A+T)Accuracy76.8—Unverified
8CHFusionAccuracy76.5—Unverified
9bc-LSTMWeighted F174.1—Unverified
10Audio + Text (Stage III)F170.5—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F166.71—Unverified
2Audio + Text (Stage III)Weighted F165.8—Unverified
3JoyfulWeighted F161.77—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F172.81—Unverified
2JoyfulWeighted F170.5—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F144.93—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F166.73—Unverified
#ModelMetricClaimedVerifiedStatus
1SMPLify-Xv2v error52.9—Unverified
#ModelMetricClaimedVerifiedStatus
1GraphSmileWeighted F174.31—Unverified