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 126–150 of 2041 papers

TitleStatusHype
A novel Fourier Adjacency Transformer for advanced EEG emotion recognitionCode1
Steering Language Model to Stable Speech Emotion Recognition via Contextual Perception and Chain of ThoughtCode1
Teleology-Driven Affective Computing: A Causal Framework for Sustained Well-Being—0
Latent Distribution Decoupling: A Probabilistic Framework for Uncertainty-Aware Multimodal Emotion RecognitionCode1
MSE-Adapter: A Lightweight Plugin Endowing LLMs with the Capability to Perform Multimodal Sentiment Analysis and Emotion RecognitionCode1
A Survey of Personalized Large Language Models: Progress and Future DirectionsCode2
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 LanguagesCode2
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
Towards Unified Music Emotion Recognition across Dimensional and Categorical ModelsCode1
Emotion Recognition and Generation: A Comprehensive Review of Face, Speech, and Text Modalities—0
SigWavNet: Learning Multiresolution Signal Wavelet Network for Speech Emotion RecognitionCode1
Milmer: a Framework for Multiple Instance Learning based Multimodal Emotion RecognitionCode1
Mini-ResEmoteNet: Leveraging Knowledge Distillation for Human-Centered Design—0
Divergent Emotional Patterns in Disinformation on Social Media? An Analysis of Tweets and TikToks about the DANA in Valencia—0
Linguistic Analysis of Sinhala YouTube Comments on Sinhala Music Videos: A Dataset Study—0
Multimodal Magic Elevating Depression Detection with a Fusion of Text and Audio Intelligence—0
Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition—0
Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition—0
HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding—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