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

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Showing 1526–1550 of 2041 papers

TitleStatusHype
A Multimodal Fusion Network For Student Emotion Recognition Based on Transformer and Tensor Product—0
A Multi-Task Learning & Generation Framework: Valence-Arousal, Action Units & Primary Expressions—0
A Multi-Task, Multi-Modal Approach for Predicting Categorical and Dimensional Emotions—0
A Multi-View Sentiment Corpus—0
AMuSE: Adaptive Multimodal Analysis for Speaker Emotion Recognition in Group Conversations—0
An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks—0
An adversarial learning framework for preserving users' anonymity in face-based emotion recognition—0
An Affective Situation Labeling System from Psychological Behaviors in Emotion Recognition—0
An Algerian Corpus and an Annotation Platform for Opinion and Emotion Analysis—0
Analysis of Basic Emotions in Texts Based on BERT Vector Representation—0
Analysis of constant-Q filterbank based representations for speech emotion recognition—0
Analysis of Resource-efficient Predictive Models for Natural Language Processing—0
Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME—0
Analyzing Speech Unit Selection for Textless Speech-to-Speech Translation—0
Analyzing the Affect of a Group of People Using Multi-modal Framework—0
Analyzing the Influence of Dataset Composition for Emotion Recognition—0
An analysis of large speech models-based representations for speech emotion recognition—0
An Application of a Runtime Epistemic Probabilistic Event Calculus to Decision-making in e-Health Systems—0
An Approach for Improving Automatic Mouth Emotion Recognition—0
An Architecture for Accelerated Large-Scale Inference of Transformer-Based Language Models—0
An Attribute-Aligned Strategy for Learning Speech Representation—0
An Audio-Video Deep and Transfer Learning Framework for Multimodal Emotion Recognition in the wild—0
An EEG-Based Multi-Modal Emotion Database with Both Posed and Authentic Facial Actions for Emotion Analysis—0
An Efficient End-to-End Transformer with Progressive Tri-modal Attention for Multi-modal Emotion Recognition—0
An Empirical Study and Improvement for Speech Emotion Recognition—0
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All datasetsEmomusicRAVDESSEMOTICFER2013MaSaC_ERCMPEDMSP-PodcastSEEDคลิปคุณพ่อให้ลูกสาวยืมโทรศัพท์และความสนุกสนาน

Benchmark Results

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