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 1651–1675 of 2041 papers

TitleStatusHype
Neural Architecture Search for Speech Emotion Recognition—0
Neural Dependency Coding inspired Multimodal Fusion—0
Neural Network architectures to classify emotions in Indian Classical Music—0
Neuromorphic Valence and Arousal Estimation—0
New Approach for an Affective Computing-Driven Quality of Experience (QoE) Prediction—0
NLP meets psychotherapy: Using predicted client emotions and self-reported client emotions to measure emotional coherence—0
Noise-Resistant Multimodal Transformer for Emotion Recognition—0
Noise robust speech emotion recognition with signal-to-noise ratio adapting speech enhancement—0
Non-Contrastive Self-supervised Learning for Utterance-Level Information Extraction from Speech—0
Non-linear frequency warping using constant-Q transformation for speech emotion recognition—0
Non-Volume Preserving-based Fusion to Group-Level Emotion Recognition on Crowd Videos—0
Normalization Before Shaking Toward Learning Symmetrically Distributed Representation Without Margin in Speech Emotion Recognition—0
Novel Dual-Channel Long Short-Term Memory Compressed Capsule Networks for Emotion Recognition—0
Novel techniques for improving NNetEn entropy calculation for short and noisy time series—0
NSEmo at EmoInt-2017: An Ensemble to Predict Emotion Intensity in Tweets—0
NUIG at EmoInt-2017: BiLSTM and SVR Ensemble to Detect Emotion Intensity—0
NUS-Emo at SemEval-2024 Task 3: Instruction-Tuning LLM for Multimodal Emotion-Cause Analysis in Conversations—0
Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words—0
Occlusion Aware Student Emotion Recognition based on Facial Action Unit Detection—0
Oculum afficit: Ocular Affect Recognition—0
Omni-Emotion: Extending Video MLLM with Detailed Face and Audio Modeling for Multimodal Emotion Analysis—0
OmniVox: Zero-Shot Emotion Recognition with Omni-LLMs—0
Once More, With Feeling: Measuring Emotion of Acting Performances in Contemporary American Film—0
On Enhancing Speech Emotion Recognition using Generative Adversarial Networks—0
On the Challenges of Sentiment Analysis for Dynamic Events—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