414 citations · 743 across the 10 of their papers we have counts for
5 papers · 1 filter
Low-complexity CNNs for Acoustic Scene Classification
Arshdeep Singh, James A King, Xubo Liu +2
This technical report describes the SurreyAudioTeam22s submission for DCASE 2022 ASC Task 1, Low-Complexity Acoustic Scene Classification (ASC). The task has two rules, (a) the ASC…
Low-complexity CNNs for Acoustic Scene Classification
Arshdeep Singh, Mark D. Plumbley
This paper presents a low-complexity framework for acoustic scene classification (ASC). Most of the frameworks designed for ASC use convolutional neural networks (CNNs) due to thei…
Surrey System for DCASE 2022 Task 5: Few-shot Bioacoustic Event Detection with Segment-level Metric Learning
Haohe Liu, Xubo Liu, Xinhao Mei +3
Few-shot audio event detection is a task that detects the occurrence time of a novel sound class given a few examples. In this work, we propose a system based on segment-level metr…
Continual Learning For On-Device Environmental Sound Classification
Yang Xiao, Xubo Liu, James King +4
Continuously learning new classes without catastrophic forgetting is a challenging problem for on-device environmental sound classification given the restrictions on computation re…
Segment-level Metric Learning for Few-shot Bioacoustic Event Detection
Haohe Liu, Xubo Liu, Xinhao Mei +3
Few-shot bioacoustic event detection is a task that detects the occurrence time of a novel sound given a few examples. Previous methods employ metric learning to build a latent spa…