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 401–450 of 2041 papers

TitleStatusHype
Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation—0
Hierarchical Adaptive Expert for Multimodal Sentiment Analysis—0
Large Language Models Meet Contrastive Learning: Zero-Shot Emotion Recognition Across LanguagesCode0
Deep Learning for Speech Emotion Recognition: A CNN Approach Utilizing Mel Spectrograms—0
Modeling speech emotion with label variance and analyzing performance across speakers and unseen acoustic conditions—0
Enhancing Multi-Label Emotion Analysis and Corresponding Intensities for Ethiopian Languages—0
Coverage-Guaranteed Speech Emotion Recognition via Calibrated Uncertainty-Adaptive Prediction Sets—0
FACE: Few-shot Adapter with Cross-view Fusion for Cross-subject EEG Emotion Recognition—0
Feature-Based Dual Visual Feature Extraction Model for Compound Multimodal Emotion RecognitionCode0
Unifying EEG and Speech for Emotion Recognition: A Two-Step Joint Learning Framework for Handling Missing EEG Data During Inference—0
Modelling Emotions in Face-to-Face Setting: The Interplay of Eye-Tracking, Personality, and Temporal Dynamics—0
United we stand, Divided we fall: Handling Weak Complementary Relationships for Audio-Visual Emotion Recognition in Valence-Arousal Space—0
Compound Expression Recognition via Large Vision-Language Models—0
Mamba-VA: A Mamba-based Approach for Continuous Emotion Recognition in Valence-Arousal SpaceCode0
Technical Approach for the EMI Challenge in the 8th Affective Behavior Analysis in-the-Wild Competition—0
Emotion Recognition with CLIP and Sequential Learning—0
CULEMO: Cultural Lenses on Emotion -- Benchmarking LLMs for Cross-Cultural Emotion Understanding—0
CALLM: Understanding Cancer Survivors' Emotions and Intervention Opportunities via Mobile Diaries and Context-Aware Language Models—0
Synthetic Data Generation of Body Motion Data by Neural Gas Network for Emotion RecognitionCode0
Heterogeneous bimodal attention fusion for speech emotion recognition—0
Multimodal Emotion Recognition and Sentiment Analysis in Multi-Party Conversation Contexts—0
Bimodal Connection Attention Fusion for Speech Emotion Recognition—0
Personalized Emotion Detection from Floor Vibrations Induced by Footsteps—0
Qieemo: Speech Is All You Need in the Emotion Recognition in Conversations—0
ECG-EmotionNet: Nested Mixture of Expert (NMoE) Adaptation of ECG-Foundation Model for Driver Emotion Recognition—0
Teleology-Driven Affective Computing: A Causal Framework for Sustained Well-Being—0
Akan Cinematic Emotions (ACE): A Multimodal Multi-party Dataset for Emotion Recognition in Movie Dialogues—0
Interpretable Concept-based Deep Learning Framework for Multimodal Human Behavior Modeling—0
A Novel Dialect-Aware Framework for the Classification of Arabic Dialects and Emotions—0
A Novel Approach to for Multimodal Emotion Recognition : Multimodal semantic information fusion—0
Enhancing Higher Education with Generative AI: A Multimodal Approach for Personalised Learning—0
RAMer: Reconstruction-based Adversarial Model for Multi-party Multi-modal Multi-label Emotion RecognitionCode0
EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models—0
Emotion Recognition and Generation: A Comprehensive Review of Face, Speech, and Text Modalities—0
Mini-ResEmoteNet: Leveraging Knowledge Distillation for Human-Centered Design—0
Multimodal Magic Elevating Depression Detection with a Fusion of Text and Audio Intelligence—0
Linguistic Analysis of Sinhala YouTube Comments on Sinhala Music Videos: A Dataset Study—0
Divergent Emotional Patterns in Disinformation on Social Media? An Analysis of Tweets and TikToks about the DANA in Valencia—0
Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition—0
HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding—0
Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition—0
Adaptive Progressive Attention Graph Neural Network for EEG Emotion Recognition—0
Why disentanglement-based speaker anonymization systems fail at preserving emotions?—0
EmoFormer: A Text-Independent Speech Emotion Recognition using a Hybrid Transformer-CNN model—0
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network—0
Representation Learning with Parameterised Quantum Circuits for Advancing Speech Emotion Recognition—0
Uncertainty Estimation in the Real World: A Study on Music Emotion Recognition—0
LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations—0
AIMA at SemEval-2024 Task 10: History-Based Emotion Recognition in Hindi-English Code-Mixed Conversations—0
Omni-Emotion: Extending Video MLLM with Detailed Face and Audio Modeling for Multimodal Emotion Analysis—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