TY - GEN
T1 - Leveraging Pre-Trained Acoustic Feature Extractor For Affective Vocal Bursts Tasks
AU - Atmaja, Bagus Tris
AU - Sasou, Akira
N1 - Publisher Copyright:
© 2022 Asia-Pacific of Signal and Information Processing Association (APSIPA).
PY - 2022
Y1 - 2022
N2 - Understanding humans' emotions is a challenge for computers. Nowadays, research on speech emotion recognition has been conducted progressively. Instead of a speech, affective information may lay on short vocal bursts (i.e., cry when sad). In this study, we evaluated a recent self-supervised learning model to extract acoustic embedding for affective vocal bursts tasks. There are four tasks investigated on both regression and classification problems. Using similar architectures, we found the effectiveness of using a pre-trained model over the baseline methods. The study is further expanded to evaluate the different number of seeds, patiences, and batch sizes on the performance of the four tasks.
AB - Understanding humans' emotions is a challenge for computers. Nowadays, research on speech emotion recognition has been conducted progressively. Instead of a speech, affective information may lay on short vocal bursts (i.e., cry when sad). In this study, we evaluated a recent self-supervised learning model to extract acoustic embedding for affective vocal bursts tasks. There are four tasks investigated on both regression and classification problems. Using similar architectures, we found the effectiveness of using a pre-trained model over the baseline methods. The study is further expanded to evaluate the different number of seeds, patiences, and batch sizes on the performance of the four tasks.
KW - affective computing
KW - affective vocal bursts
KW - pre-trained model
KW - speech emotion recognition
KW - wav2vec 2.0
UR - http://www.scopus.com/inward/record.url?scp=85139148141&partnerID=8YFLogxK
U2 - 10.23919/APSIPAASC55919.2022.9980083
DO - 10.23919/APSIPAASC55919.2022.9980083
M3 - Conference contribution
AN - SCOPUS:85139148141
T3 - Proceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
SP - 1412
EP - 1417
BT - Proceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
Y2 - 7 November 2022 through 10 November 2022
ER -