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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 726–750 of 2041 papers

TitleStatusHype
Continuous Multimodal Emotion Recognition Approach for AVEC 2017—0
ArPanEmo: An Open-Source Dataset for Fine-Grained Emotion Recognition in Arabic Online Content during COVID-19 Pandemic—0
Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages—0
Continuous Learning Based Novelty Aware Emotion Recognition System—0
A Robust Incomplete Multimodal Low-Rank Adaptation Approach for Emotion Recognition—0
Continuous Emotion Recognition with Spatiotemporal Convolutional Neural Networks—0
Continuous Emotion Recognition via Deep Convolutional Autoencoder and Support Vector Regressor—0
A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluation—0
Acted vs. Improvised: Domain Adaptation for Elicitation Approaches in Audio-Visual Emotion Recognition—0
Contextualized Emotion Recognition in Conversation as Sequence Tagging—0
"Are you okay, honey?": Recognizing Emotions among Couples Managing Diabetes in Daily Life using Multimodal Real-World Smartwatch Data—0
Contextual Emotion Recognition using Large Vision Language Models—0
Contextual Dependencies in Time-Continuous Multidimensional Affect Recognition—0
Contextual Augmentation of Pretrained Language Models for Emotion Recognition in Conversations—0
A Review of Deep Learning Techniques for Speech Processing—0
Ain't Misbehavin' -- Using LLMs to Generate Expressive Robot Behavior in Conversations with the Tabletop Robot Haru—0
Accounting for Variations in Speech Emotion Recognition with Nonparametric Hierarchical Neural Network—0
Conditioning LLMs with Emotion in Neural Machine Translation—0
Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition—0
Are Mamba-based Audio Foundation Models the Best Fit for Non-Verbal Emotion Recognition?—0
Context-Dependent Models for Predicting and Characterizing Facial Expressiveness—0
Are Large Language Models More Empathetic than Humans?—0
AIMDiT: Modality Augmentation and Interaction via Multimodal Dimension Transformation for Emotion Recognition in Conversations—0
Context-Dependent Domain Adversarial Neural Network for Multimodal Emotion Recognition—0
Are Generative Language Models Multicultural? A Study on Hausa Culture and Emotions using ChatGPT—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