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 501–550 of 2041 papers

TitleStatusHype
Decoding Human Emotions: Analyzing Multi-Channel EEG Data using LSTM Networks—0
APEX: Attention on Personality based Emotion ReXgnition Framework—0
Addressing Racial Bias in Facial Emotion Recognition—0
Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition—0
Computational Emotion Analysis From Images: Recent Advances and Future Directions—0
Deep Convolution Network Based Emotion Analysis for Automatic Detection of Mild Cognitive Impairment in the Elderly—0
Compound Expression Recognition via Large Vision-Language Models—0
A Multimodal Emotion Recognition System: Integrating Facial Expressions, Body Movement, Speech, and Spoken Language—0
AttX: Attentive Cross-Connections for Fusion of Wearable Signals in Emotion Recognition—0
Deep Evolution for Facial Emotion Recognition—0
A Cross-Corpus Speech Emotion Recognition Method Based on Supervised Contrastive Learning—0
Dynamic Graph Neural ODE Network for Multi-modal Emotion Recognition in Conversation—0
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation—0
A Peek at Peak Emotion Recognition—0
A hierarchical approach with feature selection for emotion recognition from speech—0
A breakthrough in Speech emotion recognition using Deep Retinal Convolution Neural Networks—0
Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review—0
Comparison of Gender- and Speaker-adaptive Emotion Recognition—0
A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let's Go Bus Information System—0
A Parallel Corpus of Music and Lyrics Annotated with Emotions—0
Comparison and Analysis of Deep Audio Embeddings for Music Emotion Recognition—0
A Heterogeneous Multimodal Graph Learning Framework for Recognizing User Emotions in Social Networks—0
Acquiring a Dictionary of Emotion-Provoking Events—0
FE-Adapter: Adapting Image-based Emotion Classifiers to Videos—0
Dynamic Layer Customization for Noise Robust Speech Emotion Recognition in Heterogeneous Condition Training—0
Dynamic Time-Alignment of Dimensional Annotations of Emotion using Recurrent Neural Networks—0
EMA at SemEval-2018 Task 1: Emotion Mining for Arabic—0
Comparative Study of Pre-Trained BERT Models for Code-Mixed Hindi-English Data—0
A Novel Transferability Attention Neural Network Model for EEG Emotion Recognition—0
ComFace: Facial Representation Learning with Synthetic Data for Comparing Faces—0
Combining Qualitative and Computational Approaches for Literary Analysis of Finnish Novels—0
A Novel Trajectory-based Spatial-Temporal Spectral Features for Speech Emotion Recognition—0
AHD ConvNet for Speech Emotion Classification—0
Combining Heterogeneous User Generated Data to Sense Well-being—0
A Novel Semi-supervised Meta Learning Method for Subject-transfer Brain-computer Interface—0
Acoustic-to-articulatory Speech Inversion with Multi-task Learning—0
COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognition—0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation—0
A Graph Isomorphism Network with Weighted Multiple Aggregators for Speech Emotion Recognition—0
A Bilingual Attention Network for Code-switched Emotion Prediction—0
Technical Approach for the EMI Challenge in the 8th Affective Behavior Analysis in-the-Wild Competition—0
A Novel Multi-Task Learning Method for Symbolic Music Emotion Recognition—0
CocoER: Aligning Multi-Level Feature by Competition and Coordination for Emotion Recognition—0
A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding—0
A Genetic Feature Selection Based Two-stream Neural Network for Anger Veracity Recognition—0
Acoustic and linguistic representations for speech continuous emotion recognition in call center conversations—0
CNN-n-GRU: end-to-end speech emotion recognition from raw waveform signal using CNNs and gated recurrent unit networks—0
CNN+LSTM Architecture for Speech Emotion Recognition with Data Augmentation—0
CNN based music emotion classification—0
CN-HIT-MI.T at SemEval-2020 Task 8: Memotion Analysis Based on BERT—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