SOTAVerified

Emotion Recognition

Emotion Recognition is an important area of research to enable effective human-computer interaction. Human emotions can be detected using speech signal, facial expressions, body language, and electroencephalography (EEG). Source: Using Deep Autoencoders for Facial Expression Recognition

Papers

Showing 10261050 of 2041 papers

TitleStatusHype
Emotion Recognition with Pre-Trained Transformers Using Multimodal Signals0
Leveraging Pre-Trained Acoustic Feature Extractor For Affective Vocal Bursts TasksCode0
Multimodal Emotion Recognition among Couples from Lab Settings to Daily Life using Smartwatches0
InterMulti:Multi-view Multimodal Interactions with Text-dominated Hierarchical High-order Fusion for Emotion Analysis0
Improving the Generalizability of Text-Based Emotion Detection by Leveraging Transformers with Psycholinguistic Features0
Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methods0
EffMulti: Efficiently Modeling Complex Multimodal Interactions for Emotion Analysis0
Disentangling Prosody Representations with Unsupervised Speech Reconstruction0
An Approach for Improving Automatic Mouth Emotion Recognition0
A comparative study of emotion recognition methods using facial expressions0
A survey of smart classroom: Concept, technologies and facial emotions recognition application0
Fuse and Adapt: Investigating the Use of Pre-Trained Self-Supervising Learning Models in Limited Data NLU problems0
Analysis of constant-Q filterbank based representations for speech emotion recognition0
Whose Emotion Matters? Speaking Activity Localisation without Prior KnowledgeCode0
STILN: A Novel Spatial-Temporal Information Learning Network for EEG-based Emotion Recognition0
NLP meets psychotherapy: Using predicted client emotions and self-reported client emotions to measure emotional coherence0
FAF: A novel multimodal emotion recognition approach integrating face, body and text0
Explaining (Sarcastic) Utterances to Enhance Affect Understanding in Multimodal DialoguesCode0
Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition0
Privacy against Real-Time Speech Emotion Detection via Acoustic Adversarial Evasion of Machine Learning0
Temporal-spatial Representation Learning Transformer for EEG-based Emotion Recognition0
Improving Speech Emotion Recognition with Unsupervised Speaking Style Transfer0
Deep Emotion Recognition in Textual Conversations: A SurveyCode0
Persian Emotion Detection using ParsBERT and Imbalanced Data Handling ApproachesCode0
Sentiment recognition of Italian elderly through domain adaptation on cross-corpus speech dataset0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1M2D-CLAPEmoA77.4Unverified
2M2D2EmoA76.7Unverified
3M2DEmoA76.1Unverified
4Jukebox (Pre-training: CALM)EmoA72.1Unverified
5CLMR (Pre-training: contrastive)EmoA67.8Unverified
#ModelMetricClaimedVerifiedStatus
1LogisticRegression on posteriors of xlsr-Wav2Vec2.0&bi-LSTM+AttentionAccuracy86.7Unverified
2MultiMAE-DERWAR83.61Unverified
3Intermediate-Attention-FusionAccuracy81.58Unverified
4Logistic Regression on posteriors of the CNN-14&biLSTM-GuidedSTAccuracy80.08Unverified
5ERANN-0-4Accuracy74.8Unverified
#ModelMetricClaimedVerifiedStatus
1CAGETop-3 Accuracy (%)14.73Unverified
2FocusCLIPTop-3 Accuracy (%)13.73Unverified
#ModelMetricClaimedVerifiedStatus
1VGG based5-class test accuracy66.13Unverified
#ModelMetricClaimedVerifiedStatus
1MaSaC-ERC-ZF1-score (Weighted)51.17Unverified
#ModelMetricClaimedVerifiedStatus
1BiHDMAccuracy40.34Unverified
#ModelMetricClaimedVerifiedStatus
1w2v2-L-robust-12Concordance correlation coefficient (CCC)0.64Unverified
#ModelMetricClaimedVerifiedStatus
14D-aNNAccuracy96.1Unverified
#ModelMetricClaimedVerifiedStatus
1CNN1'"1Unverified