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 …

In this paper, we presents a low-complexity deep learning frameworks for acoustic scene
classification (ASC). The proposed framework can be separated into three main steps: Front …

We propose a convolutional neural network (CNN) model based on an attention pooling
method to classify ten different acoustic scenes, participating in the acoustic scene …

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 …

The goal of Acoustic Scene Classification (ASC) is to recognise the environment in which an
audio waveform has been recorded. Recently, deep neural networks have been applied to …

This report describes our contribution to the 2017 Detection and Classification of Acoustic
Scenes and Events (DCASE) challenge. We investigated two approaches for the acoustic …

Convolutional neural networks with time-frequency feature representation for acoustic scene
classification have been attracting increasing attentions. However, most of the existing …

This paper presents a low-complexity framework for acoustic scene classification (ASC).
Most of the frameworks designed for ASC use convolutional neural networks (CNNs) due to …

Acoustic scene classification contains frequently misclassified pairs of classes that share
many common acoustic properties. Specific details can provide vital clues for distinguishing …

Deep neural networks (DNNs) have been proven to be powerful models for acoustic scene
classification tasks. State-of-the-art DNNs have millions of connections and are …