Most deep learning-based acoustic scene classification (ASC) approaches identify scenes
based on acoustic features converted from audio clips containing mixed information …

Acoustic scene classification (ASC) can be helpful for creating context awareness for
intelligent robots. Humans naturally use the relations between acoustic scenes (AS) and …

Soundscape studies typically attempt to capture the perception and understanding of sonic
environments by surveying users. However, for long-term monitoring or assessing …

In this paper, we propose lightweight deep neural networks for Acoustic Scene Classification
(ASC) and a visualization method for presenting a sound scene context. To this end, we first …

Sound classification algorithms are challenged by the natural variability of everyday sounds,
particularly for large sound class taxonomies. In order to be applicable in real-life …

Sound events in daily life carry rich information about the objective world. The composition
of these sounds affects the mood of people in a soundscape. Most previous approaches …

Most existing deep learning-based acoustic scene classification (ASC) approaches directly
utilize representations extracted from spectrograms to identify target scenes. However, these …

In this paper, we present a comprehensive analysis of Acoustic Scene Classification (ASC),
the task of identifying the scene of an audio recording from its acoustic signature. In …

Adversarial examples generated by a surrogate model typically exhibit limited transferability
to unknown target systems. To address this problem, many transferability enhancement …

Researchers increasingly look at augmenting soundscapes to reduce Behavioural and
Psychological Syndrome of Dementia (BPSD). However, methods to select suitable sounds …