Paper ID: 2208.01555

Low-complexity CNNs for Acoustic Scene Classification

Arshdeep Singh, James A King, Xubo Liu, Wenwu Wang, Mark D. Plumbley

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 framework should have maximum 128K parameters, and (b) there should be a maximum of 30 millions multiply-accumulate operations (MACs) per inference. In this report, we present low-complexity systems for ASC that follow the rules intended for the task.

Submitted: Aug 2, 2022