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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 626–650 of 2041 papers

TitleStatusHype
A Layer-Anchoring Strategy for Enhancing Cross-Lingual Speech Emotion Recognition—0
Real Time Emotion Analysis Using Deep Learning for Education, Entertainment, and Beyond—0
Generative Technology for Human Emotion Recognition: A Scope Review—0
MVGT: A Multi-view Graph Transformer Based on Spatial Relations for EEG Emotion Recognition—0
Are you sure? Analysing Uncertainty Quantification Approaches for Real-world Speech Emotion RecognitionCode0
Multi-Task Learning for Affect Analysis—0
MasonTigers at SemEval-2024 Task 10: Emotion Discovery and Flip Reasoning in Conversation with Ensemble of Transformers and Prompting—0
Are Generative Language Models Multicultural? A Study on Hausa Culture and Emotions using ChatGPT—0
Efficient Long-distance Latent Relation-aware Graph Neural Network for Multi-modal Emotion Recognition in Conversations—0
Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation—0
DASB -- Discrete Audio and Speech Benchmark—0
Apprenticeship-Inspired Elegance: Synergistic Knowledge Distillation Empowers Spiking Neural Networks for Efficient Single-Eye Emotion Recognition—0
FeedForward at SemEval-2024 Task 10: Trigger and sentext-height enriched emotion analysis in multi-party conversationsCode0
An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks—0
Finding Task-specific Subnetworks in Multi-task Spoken Language Understanding Model—0
Speech Emotion Recognition Using CNN and Its Use Case in Digital Healthcare—0
Double Multi-Head Attention Multimodal System for Odyssey 2024 Speech Emotion Recognition Challenge—0
What Does it Take to Generalize SER Model Across Datasets? A Comprehensive Benchmark—0
Exploring Multilingual Unseen Speaker Emotion Recognition: Leveraging Co-Attention Cues in Multitask LearningCode0
Exploring Self-Supervised Multi-view Contrastive Learning for Speech Emotion Recognition with Limited Annotations—0
Speech Emotion Recognition with ASR Transcripts: A Comprehensive Study on Word Error Rate and Fusion TechniquesCode0
CLDTA: Contrastive Learning based on Diagonal Transformer Autoencoder for Cross-Dataset EEG Emotion Recognition—0
Multimodal Emotion Recognition based on Facial Expressions, Speech, and EEG—0
ExHuBERT: Enhancing HuBERT Through Block Extension and Fine-Tuning on 37 Emotion DatasetsCode0
Improving Language Models for Emotion Analysis: Insights from Cognitive Science—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