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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 601–625 of 2041 papers

TitleStatusHype
Masked Graph Learning with Recurrent Alignment for Multimodal Emotion Recognition in Conversation—0
EMO-Codec: An In-Depth Look at Emotion Preservation capacity of Legacy and Neural Codec Models With Subjective and Objective Evaluations—0
A Tale of Single-channel Electroencephalogram: Devices, Datasets, Signal Processing, Applications, and Future Directions—0
EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification—0
An Explainable Fast Deep Neural Network for Emotion Recognition—0
Mapping the Technological Future: A Topic, Sentiment, and Emotion Analysis in Social Media Discourse—0
EmoCAM: Toward Understanding What Drives CNN-based Emotion Recognition—0
A Comparative Study of Transfer Learning for Emotion Recognition using CNN and Modified VGG16 Models—0
Temporal Label Hierachical Network for Compound Emotion Recognition—0
Textualized and Feature-based Models for Compound Multimodal Emotion Recognition in the WildCode0
PCQ: Emotion Recognition in Speech via Progressive Channel Querying—0
BSC-UPC at EmoSPeech-IberLEF2024: Attention Pooling for Emotion RecognitionCode0
In-Depth Analysis of Emotion Recognition through Knowledge-Based Large Language Models—0
Enhancing Facial Expression Recognition through Dual-Direction Attention Mixed Feature Networks: Application to 7th ABAW Challenge—0
MASIVE: Open-Ended Affective State Identification in English and SpanishCode0
Large Vision-Language Models as Emotion Recognizers in Context Awareness—0
SensEmo: Enabling Affective Learning through Real-time Emotion Recognition with Smartwatches—0
PSO Fuzzy XGBoost Classifier Boosted with Neural Gas Features on EEG Signals in Emotion Recognition—0
Emotion Detection through Body Gesture and Face—0
Enhancing Emotion Recognition in Incomplete Data: A Novel Cross-Modal Alignment, Reconstruction, and Refinement Framework—0
Listen and Speak Fairly: A Study on Semantic Gender Bias in Speech Integrated Large Language ModelsCode0
MSP-Podcast SER Challenge 2024: L'antenne du Ventoux Multimodal Self-Supervised Learning for Speech Emotion Recognition—0
Analyzing Speech Unit Selection for Textless Speech-to-Speech Translation—0
MERGE -- A Bimodal Audio-Lyrics Dataset for Static Music Emotion Recognition—0
A Layer-Anchoring Strategy for Enhancing Cross-Lingual Speech Emotion Recognition—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