Abstract Environmental Sound Classification (ESC) is one of the most challenging tasks in
signal processing, digital forensic and machine learning. Numerous methods have been …

Complexity of environmental sounds impose numerous challenges for their classification.
The performance of Environmental Sound Classification (ESC) depends greatly on how …

Environmental sound classification (ESC) is an increasingly relevant field of research in
recent years but has high computational overhead in its classification of environmental …

Acoustic scene classification (ASC) is an audio classification task that identifies the
environment in which sounds are recorded. Audio-related machine learning algorithms …

Future communication networks will require innovative ways to meet the rising expectations
for huge connection, low latency, and great reliability. A promising approach to increase …

Acoustic scene classification (ASC) aims to classify an audio clip based on the characteristic
of the recording environment. In this regard, deep learning based approaches have …

In this paper, we present a robust and low complexity model for Acoustic Scene
Classification (ASC), the task of identifying the scene of an audio recording. We firstly …

The paper presents an audio-based context recognition system using ensemble classifiers
with wavelet feature extraction. The device-wise classification accuracy can be achieved …

Deep learning has proven to be suitable for acoustic scene classification (ASC). Therefore, it
exhibits significant improvement in performance while using neural networks. However …

Classification of environmental sound is an equally challenging task to classification of
human speech or music. In recent years, attention mechanism has gained considerable …