ACRCNET: a small audio classification residual convolutional neural network

Hailei He; Hongjie Wan; Yuting Zhou

doi:10.1117/12.2683351

26 June 2023 ACRCNET: a small audio classification residual convolutional neural network

Hailei He, Hongjie Wan, Yuting Zhou

Proceedings Volume 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023); 1272118 (2023) https://doi.org/10.1117/12.2683351
Event: 2023 2nd International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2023, Chengdu, China

Abstract

Audio classification is widely used in our daily life. However, computing resources are limited and many audio classification datasets are generally small especially when compared to the image domain, which limits the training of large networks. Therefore, it is necessary to construct a small network with few parameters but can achieve good performance. In this paper, we propose a small Audio Classification Residual Convolutional Neural Network (AcrcNet) which is composed of two main feature extraction blocks: a time domain feature (TDF) extraction block and a high-level residual feature (HLRF) extraction block. In the TDF extraction block, the time-consuming time-frequency domain conversion is replaced with one-dimensional CNN so that time domain signals can be used as input directly. In the HLRF extraction block, we propose a Residual Convolutional (RC) module which not only deepens the depth of the network but also eliminates degradation phenomenon by using residual learning. In addition, the avgpool layer is applied at the end of the HLRF extraction block to process input of any length. In the experimental section, we use Between-Class (BC) learning to achieve good performance on the Environmental Sound Classification (ESC-50) dataset. The results of 5-fold Cross-Validation (CV) indicate that the performance of the proposed AcrcNet is better than other state-of-the-art small networks.

Citation Download Citation

Hailei He, Hongjie Wan, and Yuting Zhou "ACRCNET: a small audio classification residual convolutional neural network", Proc. SPIE 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 1272118 (26 June 2023); https://doi.org/10.1117/12.2683351

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