Fine-tuning Wav2vec for Vocal-burst Emotion Recognition

• URL: http://arxiv.org/abs/2210.00263v1
• Date: Sat, 1 Oct 2022 12:03:27 GMT
• Title: Fine-tuning Wav2vec for Vocal-burst Emotion Recognition
• Authors: Dang-Khanh Nguyen, Sudarshan Pant, Ngoc-Huynh Ho, Guee-Sang Lee, Soo-Huyng Kim, Hyung-Jeong Yang
• Abstract summary: The ACII Vocal Affective Bursts (A-VB) competition introduces a new topic in affective computing. The vocal bursts such as laughs, cries, and signs are not exploited even though they are very informative for behavior analysis. This technical report describes the method and the result of SclabCNU Team for the tasks of the challenge.
• Score: 7.910908058662372
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The ACII Affective Vocal Bursts (A-VB) competition introduces a new topic in affective computing, which is understanding emotional expression using the non-verbal sound of humans. We are familiar with emotion recognition via verbal vocal or facial expression. However, the vocal bursts such as laughs, cries, and signs, are not exploited even though they are very informative for behavior analysis. The A-VB competition comprises four tasks that explore non-verbal information in different spaces. This technical report describes the method and the result of SclabCNU Team for the tasks of the challenge. We achieved promising results compared to the baseline model provided by the organizers.

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