Acoustic Scene Classification aims to recognize the unique acoustic characteristics of an
environment. Recently, Convolutional Neural Networks (CNNs) have boosted the accuracy …

This paper address the Hanyang University team submission for the DCASE 2022
Challenge Low-Complexity Acoustic Scene Classification task. The task aims to design a …

In this work, we describe RandMasking Augment as an effective data augmentation method
for acoustic scene classification research. We concentrate on both time and frequency …

We propose a low-complexity acoustic scene classification (ASC) model structure suitable
for short-segmented audio and fine-tuning methods for generalization to multiple recording …

Deep learning models for verification systems often fail to generalize to new users and new
environments, even though they learn highly discriminative features. To address this …

Acoustic sensing has been widely exploited for the early detection of harmful situations in
urban environments: in particular, several siren identification algorithms based on deep …

There is increasing interest in the use of the LEArnable Front-end (LEAF) in a variety of
speech processing systems. However, there is a dearth of analyses of what is actually learnt …

In Automatic Speech Recognition (ASR), teacher-student (T/S) training has shown to
perform well for domain adaptation with small amount of training data. However, adaption …