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 451–500 of 2041 papers

TitleStatusHype
Could Speaker, Gender or Age Awareness be beneficial in Speech-based Emotion Recognition?—0
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition—0
A Study on the Ambiguity in Human Annotation of German Oral History Interviews for Perceived Emotion Recognition and Sentiment Analysis—0
Construction of Emotional Lexicon Using Potts Model—0
AI-Based Facial Emotion Recognition Solutions for Education: A Study of Teacher-User and Other Categories—0
Cross-Attention is Not Always Needed: Dynamic Cross-Attention for Audio-Visual Dimensional Emotion Recognition—0
Construction of a Chinese Corpus for the Analysis of the Emotionality of Metaphorical Expressions—0
Cross-Corpus Multilingual Speech Emotion Recognition: Amharic vs. Other Languages—0
Cross-cultural Emotion Classification: the Effect of Emotional Intensity and Acoustic Features—0
Cross Domain Emotion Recognition using Few Shot Knowledge Transfer—0
Construction and Annotation of a French Folkstale Corpus—0
Cross-Language Speech Emotion Recognition Using Multimodal Dual Attention Transformers—0
A Pre-trained Audio-Visual Transformer for Emotion Recognition—0
Consensus-based Distributed Quantum Kernel Learning for Speech Recognition—0
Cross Lingual Cross Corpus Speech Emotion Recognition—0
A Survey on Paralinguistics in Tamil Speech Processing—0
ConcealNet: An End-to-end Neural Network for Packet Loss Concealment in Deep Speech Emotion Recognition—0
Alzheimer's Disease Diagnosis Based on Cognitive Methods in Virtual Environments and Emotions Analysis—0
Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition—0
cross-modal fusion techniques for utterance-level emotion recognition from text and speech—0
Cross-subject Action Unit Detection with Meta Learning and Transformer-based Relation Modeling—0
Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition—0
Apprenticeship-Inspired Elegance: Synergistic Knowledge Distillation Empowers Spiking Neural Networks for Efficient Single-Eye Emotion Recognition—0
A Hybrid End-to-End Spatio-Temporal Attention Neural Network with Graph-Smooth Signals for EEG Emotion Recognition—0
Crowdsourcing and Validating Event-focused Emotion Corpora for German and English—0
Crowdsourcing a Word-Emotion Association Lexicon—0
Crowdsourcing-based Annotation of Emotions in Filipino and English Tweets—0
CrystalFeel at SemEval-2018 Task 1: Understanding and Detecting Emotion Intensity using Affective Lexicons—0
CSAT‑FTCN: A Fuzzy‑Oriented Model with Contextual Self‑attention Network for Multimodal Emotion Recognition—0
CTA-RNN: Channel and Temporal-wise Attention RNN Leveraging Pre-trained ASR Embeddings for Speech Emotion Recognition—0
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition—0
CUET-NLP@TamilNLP-ACL2022: Multi-Class Textual Emotion Detection from Social Media using Transformer—0
CULEMO: Cultural Lenses on Emotion -- Benchmarking LLMs for Cross-Cultural Emotion Understanding—0
A Transformer Architecture for Stress Detection from ECG—0
APPReddit: a Corpus of Reddit Posts Annotated for Appraisal—0
Computationally Efficient Wasserstein Loss for Structured Labels—0
APEX: Attention on Personality based Emotion ReXgnition Framework—0
Customising General Large Language Models for Specialised Emotion Recognition Tasks—0
DAGAM: A Domain Adversarial Graph Attention Model for Subject Independent EEG-Based Emotion Recognition—0
A Multi-Componential Approach to Emotion Recognition and the Effect of Personality—0
DASB -- Discrete Audio and Speech Benchmark—0
A Multilingual Natural Stress Emotion Database—0
Data Augmentation for Enhancing EEG-based Emotion Recognition with Deep Generative Models—0
Improving Speech Emotion Recognition with Unsupervised Speaking Style Transfer—0
Computational Emotion Analysis From Images: Recent Advances and Future Directions—0
Compound Expression Recognition via Large Vision-Language Models—0
DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks—0
Deciphering Emotions in Children Storybooks: A Comparative Analysis of Multimodal LLMs in Educational Applications—0
A Cross-Corpus Speech Emotion Recognition Method Based on Supervised Contrastive Learning—0
Developing emotion recognition for video conference software to support people with autism—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