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 26–50 of 2041 papers

TitleStatusHype
Investigating the Impact of Word Informativeness on Speech Emotion Recognition—0
Towards Machine Unlearning for Paralinguistic Speech Processing—0
Are Mamba-based Audio Foundation Models the Best Fit for Non-Verbal Emotion Recognition?—0
EfficientFER: EfficientNetv2 Based Deep Learning Approach for Facial Expression RecognitionCode1
Enhancing Speech Emotion Recognition with Graph-Based Multimodal Fusion and Prosodic Features for the Speech Emotion Recognition in Naturalistic Conditions Challenge at Interspeech 2025—0
Source Tracing of Synthetic Speech Systems Through Paralinguistic Pre-Trained Representations—0
PARROT: Synergizing Mamba and Attention-based SSL Pre-Trained Models via Parallel Branch Hadamard Optimal Transport for Speech Emotion Recognition—0
Learning More with Less: Self-Supervised Approaches for Low-Resource Speech Emotion Recognition—0
MELT: Towards Automated Multimodal Emotion Data Annotation by Leveraging LLM Embedded KnowledgeCode0
KEVER^2: Knowledge-Enhanced Visual Emotion Reasoning and Retrieval—0
Can Emotion Fool Anti-spoofing?—0
What About Emotions? Guiding Fine-Grained Emotion Extraction from Mobile App ReviewsCode0
Learning Annotation Consensus for Continuous Emotion Recognition—0
Inceptive Transformers: Enhancing Contextual Representations through Multi-Scale Feature Learning Across Domains and Languages—0
EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition—0
Knowledge-Aligned Counterfactual-Enhancement Diffusion Perception for Unsupervised Cross-Domain Visual Emotion Recognition—0
EmoSphere-SER: Enhancing Speech Emotion Recognition Through Spherical Representation with Auxiliary ClassificationCode2
Improving Speech Emotion Recognition Through Cross Modal Attention Alignment and Balanced Stacking ModelCode0
ALAS: Measuring Latent Speech-Text Alignment For Spoken Language Understanding In Multimodal LLMs—0
Contrastive Distillation of Emotion Knowledge from LLMs for Zero-Shot Emotion RecognitionCode0
CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-trainingCode11
Audio-to-Audio Emotion Conversion With Pitch And Duration Style Transfer—0
ABHINAYA -- A System for Speech Emotion Recognition In Naturalistic Conditions ChallengeCode0
Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning—0
MIKU-PAL: An Automated and Standardized Multi-Modal Method for Speech Paralinguistic and Affect Labeling—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