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 1226–1250 of 2041 papers

TitleStatusHype
Think out Loud: Emotion Deducing Explanation in Dialogues—0
THU\_NGN at SemEval-2019 Task 3: Dialog Emotion Classification using Attentional LSTM-CNN—0
TNTC: two-stream network with transformer-based complementarity for gait-based emotion recognition—0
Tollywood Emotions: Annotation of Valence-Arousal in Telugu Song Lyrics—0
Tools for Digital Humanities: Enabling Access to the Old Occitan Romance of Flamenca—0
Topic-Based Chinese Message Sentiment Analysis: A Multilayered Analysis System—0
Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition—0
Toward a Dialogue System Using a Large Language Model to Recognize User Emotions with a Camera—0
Toward end-to-end interpretable convolutional neural networks for waveform signals—0
Towards a Common Speech Analysis Engine—0
Towards Advanced Speech Signal Processing: A Statistical Perspective on Convolution-Based Architectures and its Applications—0
Towards adversarial learning of speaker-invariant representation for speech emotion recognition—0
Towards a General Deep Feature Extractor for Facial Expression Recognition—0
Towards a Generative Approach for Emotion Detection and Reasoning—0
Towards A Robust Group-level Emotion Recognition via Uncertainty-Aware Learning—0
Towards Label-Agnostic Emotion Embeddings—0
Iterative Distillation for Better Uncertainty Estimates in Multitask Emotion Recognition—0
Towards Bi-Hemispheric Emotion Mapping through EEG: A Dual-Stream Neural Network Approach—0
Towards Context-Aware Emotion Recognition Debiasing from a Causal Demystification Perspective via De-confounded Training—0
Towards Emotion-aided Multi-modal Dialogue Act Classification—0
Towards Emotion-Based Synthetic Consciousness: Using LLMs to Estimate Emotion Probability Vectors—0
Towards Emotion Recognition: A Persistent Entropy Application—0
Towards emotion recognition for virtual environments: an evaluation of EEG features on benchmark dataset—0
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features—0
Towards Interpretable and Transferable Speech Emotion Recognition: Latent Representation Based Analysis of Features, Methods and Corpora—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