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Speech Emotion Recognition

Speech Emotion Recognition is a task of speech processing and computational paralinguistics that aims to recognize and categorize the emotions expressed in spoken language. The goal is to determine the emotional state of a speaker, such as happiness, anger, sadness, or frustration, from their speech patterns, such as prosody, pitch, and rhythm.

For multimodal emotion recognition, please upload your result to Multimodal Emotion Recognition on IEMOCAP

Papers

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Showing 51–100 of 431 papers

TitleStatusHype
Odyssey 2024 - Speech Emotion Recognition Challenge: Dataset, Baseline Framework, and ResultsCode1
A vector quantized masked autoencoder for speech emotion recognitionCode1
Large Raw Emotional Dataset with Aggregation MechanismCode1
Efficient Speech Emotion Recognition Using Multi-Scale CNN and AttentionCode1
Cross-Lingual Cross-Age Group Adaptation for Low-Resource Elderly Speech Emotion RecognitionCode1
EmoNet: A Transfer Learning Framework for Multi-Corpus Speech Emotion RecognitionCode1
EmoGator: A New Open Source Vocal Burst Dataset with Baseline Machine Learning Classification MethodologiesCode1
Attribute Inference Attack of Speech Emotion Recognition in Federated Learning SettingsCode1
SERAB: A multi-lingual benchmark for speech emotion recognitionCode1
Speech Emotion Recognition with Global-Aware Fusion on Multi-scale Feature RepresentationCode1
Light-SERNet: A lightweight fully convolutional neural network for speech emotion recognitionCode1
Leveraging Pre-Trained Acoustic Feature Extractor For Affective Vocal Bursts TasksCode0
Leveraging Content and Acoustic Representations for Speech Emotion RecognitionCode0
Audio Explanation Synthesis with Generative Foundation ModelsCode0
Analysis of Self-Supervised Learning and Dimensionality Reduction Methods in Clustering-Based Active Learning for Speech Emotion RecognitionCode0
Leveraged Mel spectrograms using Harmonic and Percussive Components in Speech Emotion RecognitionCode0
A low latency attention module for streaming self-supervised speech representation learningCode0
Attentive Modality Hopping Mechanism for Speech Emotion RecognitionCode0
Learning Speech Emotion Representations in the Quaternion DomainCode0
ABHINAYA -- A System for Speech Emotion Recognition In Naturalistic Conditions ChallengeCode0
Learning Robust Self-attention Features for Speech Emotion Recognition with Label-adaptive MixupCode0
Learning Rate CurriculumCode0
A multimodal dynamical variational autoencoder for audiovisual speech representation learningCode0
Attention Based Fully Convolutional Network for Speech Emotion RecognitionCode0
Attention-Augmented End-to-End Multi-Task Learning for Emotion Prediction from SpeechCode0
Label Uncertainty Modeling and Prediction for Speech Emotion Recognition using t-DistributionsCode0
Large Language Models Meet Contrastive Learning: Zero-Shot Emotion Recognition Across LanguagesCode0
A Systematic Evaluation of Adversarial Attacks against Speech Emotion Recognition ModelsCode0
Is Everything Fine, Grandma? Acoustic and Linguistic Modeling for Robust Elderly Speech Emotion RecognitionCode0
Iterative Feature Boosting for Explainable Speech Emotion RecognitionCode0
Integrating Recurrence Dynamics for Speech Emotion RecognitionCode0
Improving Speech Emotion Recognition in Under-Resourced Languages via Speech-to-Speech Translation with Bootstrapping Data SelectionCode0
INTERSPEECH 2009 Emotion Challenge Revisited: Benchmarking 15 Years of Progress in Speech Emotion RecognitionCode0
Knowledge Transfer For On-Device Speech Emotion Recognition with Neural Structured LearningCode0
Learning Alignment for Multimodal Emotion Recognition from SpeechCode0
MEDUSA: A Multimodal Deep Fusion Multi-Stage Training Framework for Speech Emotion Recognition in Naturalistic ConditionsCode0
Fine-grained Speech Sentiment Analysis in Chinese Psychological Support Hotlines Based on Large-scale Pre-trained ModelCode0
Exploring Multilingual Unseen Speaker Emotion Recognition: Leveraging Co-Attention Cues in Multitask LearningCode0
A speech corpus of Quechua Collao for automatic dimensional emotion recognitionCode0
Fixed-MAML for Few Shot Classification in Multilingual Speech Emotion RecognitionCode0
A Change of Heart: Improving Speech Emotion Recognition through Speech-to-Text Modality ConversionCode0
ExHuBERT: Enhancing HuBERT Through Block Extension and Fine-Tuning on 37 Emotion DatasetsCode0
Multi-modal Speech Emotion Recognition via Feature Distribution Adaptation NetworkCode0
Filter-based multi-task cross-corpus feature learning for speech emotion recognitionCode0
Evaluating Gammatone Frequency Cepstral Coefficients with Neural Networks for Emotion Recognition from SpeechCode0
Are you sure? Analysing Uncertainty Quantification Approaches for Real-world Speech Emotion RecognitionCode0
Multi-Teacher Language-Aware Knowledge Distillation for Multilingual Speech Emotion RecognitionCode0
Improving Speech Emotion Recognition Through Cross Modal Attention Alignment and Balanced Stacking ModelCode0
Explaining Deep Learning Embeddings for Speech Emotion Recognition by Predicting Interpretable Acoustic FeaturesCode0
A Dataset for Speech Emotion Recognition in Greek Theatrical PlaysCode0
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All datasetsCREMA-DIEMOCAPRAVDESSMSP-Podcast (Activation)MSP-Podcast (Dominance)MSP-Podcast (Valence)BERStRESDDusha CrowdDusha PodcastEMODBEmoDB Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Vertically long patch ViTAccuracy94.07—Unverified
2ConformerXL-PAccuracy88.2—Unverified
3CoordViTAccuracy82.96—Unverified
4SepTr + LeRaCAccuracy70.95—Unverified
5SepTrAccuracy70.47—Unverified
6ResNet-18 + SPELAccuracy68.12—Unverified
7ViTAccuracy67.81—Unverified
8ResNet-18 + PyNADAAccuracy65.15—Unverified
9GRUAccuracy55.01—Unverified
#ModelMetricClaimedVerifiedStatus
1SER with MTLUA CV0.78—Unverified
2emoDARTSUA CV0.77—Unverified
3LSTM+FCWA0.76—Unverified
4TAPWA CV0.74—Unverified
5SYSCOMB: BLSTMATT with CSA (session5)UA0.74—Unverified
6Partially Fine-tuned HuBERT LargeWA CV0.73—Unverified
7CNN - DARTSUA0.7—Unverified
8CNN+LSTMUA0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1VQ-MAE-S-12 (Frame) + Query2EmoAccuracy84.1—Unverified
2CNN-X (Shallow CNN)Accuracy82.99—Unverified
3xlsr-Wav2Vec2.0(FineTuning)Accuracy81.82—Unverified
4CNN-14 (Fine-Tuning)Accuracy76.58—Unverified
5AlexNet (FineTuning)Accuracy61.67—Unverified
#ModelMetricClaimedVerifiedStatus
1wav2small-TeacherCCC0.76—Unverified
2wavlmCCC0.75—Unverified
3w2v2-L-robust-12CCC0.75—Unverified
4preCPCCCC0.71—Unverified
#ModelMetricClaimedVerifiedStatus
1wav2small-TeacherCCC0.68—Unverified
2wavlmCCC0.67—Unverified
3w2v2-L-robust-12CCC0.66—Unverified
4preCPCCCC0.64—Unverified
#ModelMetricClaimedVerifiedStatus
1wav2small-TeacherCCC0.68—Unverified
2wavlmCCC0.65—Unverified
3w2v2-L-robust-12CCC0.64—Unverified
4preCPCCCC0.38—Unverified
#ModelMetricClaimedVerifiedStatus
1DAWN-hidden-SVMUnweighted Accuracy (UA)32.1—Unverified
2Wav2Small-VAD-SVMUnweighted Accuracy (UA)23.3—Unverified
3Speechbrain Wav2Vec2Unweighted Accuracy (UA)20.7—Unverified
#ModelMetricClaimedVerifiedStatus
1emotion2vec+baseWeighted Accuracy (WA)79.4—Unverified
2emotion2vec+largeWeighted Accuracy (WA)69.5—Unverified
3emotion2vecWeighted Accuracy (WA)64.75—Unverified
#ModelMetricClaimedVerifiedStatus
1Dusha baselineMacro F10.77—Unverified
#ModelMetricClaimedVerifiedStatus
1Dusha baselineMacro F10.54—Unverified
#ModelMetricClaimedVerifiedStatus
1VGG-optiVMD1:1 Accuracy96.09—Unverified
#ModelMetricClaimedVerifiedStatus
1VQ-MAE-S-12 (Frame) + Query2EmoAccuracy90.2—Unverified
#ModelMetricClaimedVerifiedStatus
1PyResNetUnweighted Accuracy (UA)0.43—Unverified
#ModelMetricClaimedVerifiedStatus
1emoDARTSUA0.66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMCCC (Arousal)0.76—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN (1D)Unweighted Accuracy65.2—Unverified