IERP 2024: Induced Emotion Recognition with Personality Characteristics Challenge 2024

The IERP 2024 Challenge is part of the ISCSLP 2024 Competition and Challenge track, aiming to explore the application of personality characteristics in emotion recognition. Existing emotion recognition technologies primarily focus on improving the accuracy of discrete and dimensional emotions, limiting their application scope. However, emotion is closely related to personality, and individuals with different personality traits exhibit distinct emotional expressions. Therefore, integrating personality characteristics into emotion recognition systems can enhance their accuracy and adaptability, holding significant research value. The IERP 2024 Challenge provides a large-scale emotional dataset with personality trait labels and includes two tracks: Track 1: Emotion Recognition Based on Audio and Text Modality: Utilize the provided speech features to recognize the scores of eight emotions ranging from 1 to 5, where 1 represents none and 5 represents the highest degree. Track 2: Multimodal Emotion Recognition: Utilize speech features, text features, and video to design an effective emotion classification method. The emotion types, score ranges, and speech features are the same as Track 1, with the added challenge of incorporating visual information. The challenge offers a platform for researchers and developers to showcase their skills, advance emotion recognition technology, and promote its application in diverse fields.

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Publication Details

Published
2024-11-07
DOI
https://doi.org/10.1109/iscslp63861.2024.10800484
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00

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article

IERP 2024: Induced Emotion Recognition with Personality Characteristics Challenge 2024

Shan Liang, Zheng Lian, Bin Liu, Cong Cai et al.
Emotion and Mood Recognition
article

IERP 2024: Induced Emotion Recognition with Personality Characteristics Challenge 2024

Shan Liang, Zheng Lian, Bin Liu, Cong Cai, Xuefei Liu, Kang Zhu, Zhenhua Cheng
article en

Abstract

The IERP 2024 Challenge is part of the ISCSLP 2024 Competition and Challenge track, aiming to explore the application of personality characteristics in emotion recognition. Existing emotion recognition technologies primarily focus on improving the accuracy of discrete and dimensional emotions, limiting their application scope. However, emotion is closely related to personality, and individuals with different personality traits exhibit distinct emotional expressions. Therefore, integrating personality characteristics into emotion recognition systems can enhance their accuracy and adaptability, holding significant research value. The IERP 2024 Challenge provides a large-scale emotional dataset with personality trait labels and includes two tracks: Track 1: Emotion Recognition Based on Audio and Text Modality: Utilize the provided speech features to recognize the scores of eight emotions ranging from 1 to 5, where 1 represents none and 5 represents the highest degree. Track 2: Multimodal Emotion Recognition: Utilize speech features, text features, and video to design an effective emotion classification method. The emotion types, score ranges, and speech features are the same as Track 1, with the added challenge of incorporating visual information. The challenge offers a platform for researchers and developers to showcase their skills, advance emotion recognition technology, and promote its application in diverse fields.

Beijing Institute of Technology (CN), Anhui University (CN), Chinese Academy of Sciences (CN), University of Chinese Academy of Sciences (CN), Xi’an Jiaotong-Liverpool University (CN)
National Natural Science Foundation of China
Gender equality
Openalex Percentile: Top 71%
Emotion and Mood Recognition
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