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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 1–50 of 2041 papers

TitleStatusHype
Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in ConversationCode0
Camera-based implicit mind reading by capturing higher-order semantic dynamics of human gaze within environmental context—0
A Robust Incomplete Multimodal Low-Rank Adaptation Approach for Emotion Recognition—0
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in ConversationCode0
CAST-Phys: Contactless Affective States Through Physiological signals Database—0
Exploring Remote Physiological Signal Measurement under Dynamic Lighting Conditions at Night: Dataset, Experiment, and AnalysisCode1
How to Retrieve Examples in In-context Learning to Improve Conversational Emotion Recognition using Large Language Models?—0
Emotion Detection on User Front-Facing App Interfaces for Enhanced Schedule Optimization: A Machine Learning Approach—0
MATER: Multi-level Acoustic and Textual Emotion Representation for Interpretable Speech Emotion Recognition—0
Infant Cry Emotion Recognition Using Improved ECAPA-TDNN with Multiscale Feature Fusion and Attention EnhancementCode0
Reading Smiles: Proxy Bias in Foundation Models for Facial Emotion Recognition—0
Deciphering Emotions in Children Storybooks: A Comparative Analysis of Multimodal LLMs in Educational Applications—0
Optimizing Multilingual Text-To-Speech with Accents & Emotions—0
GSDNet: Revisiting Incomplete Multimodal-Diffusion from Graph Spectrum Perspective for Conversation Emotion Recognition—0
Developing a High-performance Framework for Speech Emotion Recognition in Naturalistic Conditions Challenge for Emotional Attribute Prediction—0
Towards Robust Multimodal Emotion Recognition under Missing Modalities and Distribution ShiftsCode1
MEDUSA: A Multimodal Deep Fusion Multi-Stage Training Framework for Speech Emotion Recognition in Naturalistic ConditionsCode0
Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME—0
CoMuMDR: Code-mixed Multi-modal Multi-domain corpus for Discourse paRsing in conversationsCode0
Multi-Teacher Language-Aware Knowledge Distillation for Multilingual Speech Emotion RecognitionCode0
Beyond Classification: Towards Speech Emotion Reasoning with Multitask AudioLLMs—0
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition—0
EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition—0
Prosodic Structure Beyond Lexical Content: A Study of Self-Supervised Learning—0
HYFuse: Aligning Heterogeneous Speech Pre-Trained Representations in Hyperbolic Space for Speech Emotion Recognition—0
Investigating the Impact of Word Informativeness on Speech Emotion Recognition—0
Towards Machine Unlearning for Paralinguistic Speech Processing—0
Are Mamba-based Audio Foundation Models the Best Fit for Non-Verbal Emotion Recognition?—0
EfficientFER: EfficientNetv2 Based Deep Learning Approach for Facial Expression RecognitionCode1
Enhancing Speech Emotion Recognition with Graph-Based Multimodal Fusion and Prosodic Features for the Speech Emotion Recognition in Naturalistic Conditions Challenge at Interspeech 2025—0
Source Tracing of Synthetic Speech Systems Through Paralinguistic Pre-Trained Representations—0
PARROT: Synergizing Mamba and Attention-based SSL Pre-Trained Models via Parallel Branch Hadamard Optimal Transport for Speech Emotion Recognition—0
Learning More with Less: Self-Supervised Approaches for Low-Resource Speech Emotion Recognition—0
MELT: Towards Automated Multimodal Emotion Data Annotation by Leveraging LLM Embedded KnowledgeCode0
KEVER^2: Knowledge-Enhanced Visual Emotion Reasoning and Retrieval—0
Can Emotion Fool Anti-spoofing?—0
What About Emotions? Guiding Fine-Grained Emotion Extraction from Mobile App ReviewsCode0
Learning Annotation Consensus for Continuous Emotion Recognition—0
Inceptive Transformers: Enhancing Contextual Representations through Multi-Scale Feature Learning Across Domains and Languages—0
EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition—0
Knowledge-Aligned Counterfactual-Enhancement Diffusion Perception for Unsupervised Cross-Domain Visual Emotion Recognition—0
EmoSphere-SER: Enhancing Speech Emotion Recognition Through Spherical Representation with Auxiliary ClassificationCode2
Improving Speech Emotion Recognition Through Cross Modal Attention Alignment and Balanced Stacking ModelCode0
ALAS: Measuring Latent Speech-Text Alignment For Spoken Language Understanding In Multimodal LLMs—0
Contrastive Distillation of Emotion Knowledge from LLMs for Zero-Shot Emotion RecognitionCode0
CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-trainingCode11
Audio-to-Audio Emotion Conversion With Pitch And Duration Style Transfer—0
ABHINAYA -- A System for Speech Emotion Recognition In Naturalistic Conditions ChallengeCode0
Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning—0
MIKU-PAL: An Automated and Standardized Multi-Modal Method for Speech Paralinguistic and Affect Labeling—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