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SotA/Speech/Speech Emotion Recognition

Speech Emotion Recognition

35 benchmarks431 papers

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

Benchmarks

Speech Emotion Recognition on CREMA-D

Accuracy

Speech Emotion Recognition on HUME-VB

Concordance correlation coefficient (CCC)Average Recall

Speech Emotion Recognition on IEMOCAP

WAWA CVUAUA CVF1

Speech Emotion Recognition on MSP-Podcast (Activation)

CCC

Speech Emotion Recognition on MSP-Podcast (Dominance)

CCC

Speech Emotion Recognition on MSP-Podcast (Valence)

CCC

Speech Emotion Recognition on BERSt

Unweighted Accuracy (UA)Weighted Accuracy (WA)

Speech Emotion Recognition on RESD

Weighted Accuracy (WA)Unweighted Accuracy (UA)Weighted F1

Speech Emotion Recognition on Dusha Crowd

Macro F1UAWA

Speech Emotion Recognition on Dusha Podcast

Macro F1UAWA

Speech Emotion Recognition on EMODB

1:1 Accuracy

Speech Emotion Recognition on EmoDB Dataset

AccuracyF1

Speech Emotion Recognition on LSSED

Unweighted Accuracy (UA)

Speech Emotion Recognition on MSP-IMPROV

UA

Speech Emotion Recognition on Quechua-SER

CCC (Arousal)CCC (Valence)

Speech Emotion Recognition on RAVDESS

AccuracyF1 ScorePrecisionRecallF1

Speech Emotion Recognition on ShEMO

Unweighted Accuracy