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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1701–1750 of 2041 papers

TitleStatusHype
CNN+LSTM Architecture for Speech Emotion Recognition with Data Augmentation—0
CNN-n-GRU: end-to-end speech emotion recognition from raw waveform signal using CNNs and gated recurrent unit networks—0
CocoER: Aligning Multi-Level Feature by Competition and Coordination for Emotion Recognition—0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation—0
COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognition—0
Combining Heterogeneous User Generated Data to Sense Well-being—0
Combining Qualitative and Computational Approaches for Literary Analysis of Finnish Novels—0
ComFace: Facial Representation Learning with Synthetic Data for Comparing Faces—0
Comparative Study of Pre-Trained BERT Models for Code-Mixed Hindi-English Data—0
Comparison and Analysis of Deep Audio Embeddings for Music Emotion Recognition—0
Comparison of Gender- and Speaker-adaptive Emotion Recognition—0
Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review—0
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation—0
Compound Expression Recognition via Large Vision-Language Models—0
Computational Emotion Analysis From Images: Recent Advances and Future Directions—0
Computationally Efficient Wasserstein Loss for Structured Labels—0
ConcealNet: An End-to-end Neural Network for Packet Loss Concealment in Deep Speech Emotion Recognition—0
Consensus-based Distributed Quantum Kernel Learning for Speech Recognition—0
Construction and Annotation of a French Folkstale Corpus—0
Construction of a Chinese Corpus for the Analysis of the Emotionality of Metaphorical Expressions—0
Construction of Emotional Lexicon Using Potts Model—0
Construction of English-French Multimodal Affective Conversational Corpus from TV Dramas—0
Construction of Japanese Audio-Visual Emotion Database and Its Application in Emotion Recognition—0
Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias—0
Context-aware Cascade Attention-based RNN for Video Emotion Recognition—0
Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis—0
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation—0
Context-Dependent Domain Adversarial Neural Network for Multimodal Emotion Recognition—0
Context-Dependent Models for Predicting and Characterizing Facial Expressiveness—0
Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition—0
Contextual Augmentation of Pretrained Language Models for Emotion Recognition in Conversations—0
Contextual Dependencies in Time-Continuous Multidimensional Affect Recognition—0
Contextual Emotion Recognition using Large Vision Language Models—0
Contextualized Emotion Recognition in Conversation as Sequence Tagging—0
Continuous Emotion Recognition via Deep Convolutional Autoencoder and Support Vector Regressor—0
Continuous Emotion Recognition with Spatiotemporal Convolutional Neural Networks—0
Continuous Learning Based Novelty Aware Emotion Recognition System—0
Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages—0
Continuous Multimodal Emotion Recognition Approach for AVEC 2017—0
Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition—0
Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition—0
Contrastive Unsupervised Learning for Speech Emotion Recognition—0
Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning—0
Conversational Emotion Analysis via Attention Mechanisms—0
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos—0
Converting Anyone's Voice: End-to-End Expressive Voice Conversion with a Conditional Diffusion Model—0
Converting Sentiment Annotated Data to Emotion Annotated Data—0
Convolutional and Recurrent Neural Networks for Spoken Emotion Recognition—0
Convolutional Attention Networks for Multimodal Emotion Recognition from Speech and Text Data—0
Convolutional Neural Network Approach for EEG-based Emotion Recognition using Brain Connectivity and its Spatial Information—0
Show:102550
← PrevPage 35 of 41Next →
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