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 26–50 of 2041 papers

TitleStatusHype
HiCMAE: Hierarchical Contrastive Masked Autoencoder for Self-Supervised Audio-Visual Emotion RecognitionCode2
Multimodal Prompt Learning with Missing Modalities for Sentiment Analysis and Emotion RecognitionCode2
UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion RecognitionCode2
EMO-SUPERB: An In-depth Look at Speech Emotion RecognitionCode2
EmoSphere-SER: Enhancing Speech Emotion Recognition Through Spherical Representation with Auxiliary ClassificationCode2
EmT: A Novel Transformer for Generalized Cross-subject EEG Emotion RecognitionCode2
Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 TasksCode2
Dawn of the transformer era in speech emotion recognition: closing the valence gapCode2
EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion AnalysisCode2
COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsCode2
EMOCA: Emotion Driven Monocular Face Capture and AnimationCode2
CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AICode2
EmoBench: Evaluating the Emotional Intelligence of Large Language ModelsCode2
Feature Fusion Based on Mutual-Cross-Attention Mechanism for EEG Emotion RecognitionCode2
Towards Interpretable Mental Health Analysis with Large Language ModelsCode2
Are We There Yet? A Brief Survey of Music Emotion Prediction Datasets, Models and Outstanding ChallengesCode2
A Survey of Personalized Large Language Models: Progress and Future DirectionsCode2
audino: A Modern Annotation Tool for Audio and SpeechCode2
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPTCode2
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
Compact Graph Architecture for Speech Emotion RecognitionCode1
CoMPM: Context Modeling with Speaker’s Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal NuancesCode1
Accuracy enhancement method for speech emotion recognition from spectrogram using temporal frequency correlation and positional information learning through knowledge transferCode1
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
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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