Low-complexity CNNs for Acoustic Scene Classification
This is an incremental technical report for a specific competition task in audio processing.
The authors tackled the problem of acoustic scene classification under strict computational constraints, presenting a system that adheres to a maximum of 128K parameters and 30 million MACs per inference for the DCASE 2022 task.
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.