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Speech Emotion Recognition
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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
논문
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Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition
Is It Still Fair? Investigating Gender Fairness in Cross-Corpus Speech Emotion Recognition
learning discriminative features from spectrograms using center loss for speech emotion recognition
Metadata-Enhanced Speech Emotion Recognition: Augmented Residual Integration and Co-Attention in Two-Stage Fine-Tuning
Mouth Articulation-Based Anchoring for Improved Cross-Corpus Speech Emotion Recognition
Enhanced Speech Emotion Recognition with Efficient Channel Attention Guided Deep CNN-BiLSTM Framework
Emotional Vietnamese Speech-Based Depression Diagnosis Using Dynamic Attention Mechanism
WavFusion: Towards wav2vec 2.0 Multimodal Speech Emotion Recognition
A Cross-Corpus Speech Emotion Recognition Method Based on Supervised Contrastive Learning
Once More, With Feeling: Measuring Emotion of Acting Performances in Contemporary American Film
Improvement and Implementation of a Speech Emotion Recognition Model Based on Dual-Layer LSTM
Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition
Multi-modal Speech Emotion Recognition via Feature Distribution Adaptation Network
Improving Speech-based Emotion Recognition with Contextual Utterance Analysis and LLMs
A Survey on Speech Large Language Models
Investigating Effective Speaker Property Privacy Protection in Federated Learning for Speech Emotion Recognition
Enhancing Speech Emotion Recognition through Segmental Average Pooling of Self-Supervised Learning Features
SeQuiFi: Mitigating Catastrophic Forgetting in Speech Emotion Recognition with Sequential Class-Finetuning
Multi-View Multi-Task Modeling with Speech Foundation Models for Speech Forensic Tasks
Can We Estimate Purchase Intention Based on Zero-shot Speech Emotion Recognition?
Audio Explanation Synthesis with Generative Foundation Models
A Cross-Lingual Meta-Learning Method Based on Domain Adaptation for Speech Emotion Recognition
Multi-Scale Temporal Transformer For Speech Emotion Recognition
Two-stage Framework for Robust Speech Emotion Recognition Using Target Speaker Extraction in Human Speech Noise Conditions
Exploring Acoustic Similarity in Emotional Speech and Music via Self-Supervised Representations
Cross-Lingual Speech Emotion Recognition: Humans vs. Self-Supervised Models
Improving Speech Emotion Recognition in Under-Resourced Languages via Speech-to-Speech Translation with Bootstrapping Data Selection
TBDM-Net: Bidirectional Dense Networks with Gender Information for Speech Emotion Recognition
Personalized Speech Emotion Recognition in Human-Robot Interaction using Vision Transformers
Stimulus Modality Matters: Impact of Perceptual Evaluations from Different Modalities on Speech Emotion Recognition System Performance
Turbo your multi-modal classification with contrastive learning
Explaining Deep Learning Embeddings for Speech Emotion Recognition by Predicting Interpretable Acoustic Features
Leveraging Content and Acoustic Representations for Speech Emotion Recognition
Consensus-based Distributed Quantum Kernel Learning for Speech Recognition
Searching for Effective Preprocessing Method and CNN-based Architecture with Efficient Channel Attention on Speech Emotion Recognition
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