SOTAVerified

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

Showing 110 of 431 papers

TitleStatusHype
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in ConversationCode0
MATER: Multi-level Acoustic and Textual Emotion Representation for Interpretable Speech Emotion Recognition0
Developing a High-performance Framework for Speech Emotion Recognition in Naturalistic Conditions Challenge for Emotional Attribute Prediction0
MEDUSA: A Multimodal Deep Fusion Multi-Stage Training Framework for Speech Emotion Recognition in Naturalistic ConditionsCode0
Multi-Teacher Language-Aware Knowledge Distillation for Multilingual Speech Emotion RecognitionCode0
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition0
EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition0
HYFuse: Aligning Heterogeneous Speech Pre-Trained Representations in Hyperbolic Space for Speech Emotion Recognition0
Investigating the Impact of Word Informativeness on Speech Emotion Recognition0
Are Mamba-based Audio Foundation Models the Best Fit for Non-Verbal Emotion Recognition?0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1wav2small-TeacherCCC0.68Unverified
2wavlmCCC0.65Unverified
3w2v2-L-robust-12CCC0.64Unverified
4preCPCCCC0.38Unverified