TY - GEN
T1 - An Ensemble Deep-Learning System for Few-Shot Bioacoustic Event Detection
AU - Zhang, Jianqian
AU - Liu, Miao
AU - Wang, Jing
AU - Hu, Chenguang
AU - Peng, Jiawei
AU - Li, Kaige
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Human are good at identifying new objects from only a few number of samples. Inspired by the rapid learning ability of humans, few-shot bioacoustic event detection task based on machine learning method has attracted more attention lately. In this paper, we formulated an ensemble deep-learning system to address the task, incorporating an enhanced prototypical network and transductive inference methodology. We have submitted our models to Task 5 of the Detection and Classification of Acoustic Scenes and Events 2022 (DCASE2022) challenge, and got F-measure of 64.8% on the validation set as our best score. In the final competition, our system got F-measure of 44.3% on the evaluation set.
AB - Human are good at identifying new objects from only a few number of samples. Inspired by the rapid learning ability of humans, few-shot bioacoustic event detection task based on machine learning method has attracted more attention lately. In this paper, we formulated an ensemble deep-learning system to address the task, incorporating an enhanced prototypical network and transductive inference methodology. We have submitted our models to Task 5 of the Detection and Classification of Acoustic Scenes and Events 2022 (DCASE2022) challenge, and got F-measure of 64.8% on the validation set as our best score. In the final competition, our system got F-measure of 44.3% on the evaluation set.
KW - bioacoustic event detection
KW - DCASE
KW - few-shot task
KW - prototypical networks
KW - transductive inference
UR - http://www.scopus.com/inward/record.url?scp=85194133265&partnerID=8YFLogxK
U2 - 10.1109/ACAIT60137.2023.10528451
DO - 10.1109/ACAIT60137.2023.10528451
M3 - Conference contribution
AN - SCOPUS:85194133265
T3 - Proceedings of 2023 7th Asian Conference on Artificial Intelligence Technology, ACAIT 2023
SP - 192
EP - 197
BT - Proceedings of 2023 7th Asian Conference on Artificial Intelligence Technology, ACAIT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th Asian Conference on Artificial Intelligence Technology, ACAIT 2023
Y2 - 10 November 2023 through 12 November 2023
ER -