The number of publications on acoustic scene classification (ASC) in environmental audio
recordings has constantly increased over the last few years. This was mainly stimulated by …

Monitoring of human and social activities is becoming increasingly pervasive in our living
environment for public security and safety applications. The recognition of suspicious events …

Public evaluation campaigns and datasets promote active development in target research
areas, allowing direct comparison of algorithms. The second edition of the challenge on …

Spectrogram representations of acoustic scenes have achieved competitive performance for
acoustic scene classification. Yet, the spectrogram alone does not take into account a …

This paper presents a novel application of convolutional neural networks (CNNs) for the task
of acoustic scene classification (ASC). We here propose the use of a CNN trained to classify …

This paper describes our contribution to the Acoustic Scene Classification task of the IEEE
AASP Challenge on Detection and Classification of Acoustic Scenes and Events (DCASE …

We present an overview of the challenge entries for the Acoustic Scene Classification task of
DCASE 2017 Challenge. Being the most popular task of the challenge, acoustic scene …

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 …

This article proposes an encoder-decoder network model for Acoustic Scene Classification
(ASC), the task of identifying the scene of an audio recording from its acoustic signature. We …

There are lots of research papers for ASC, and in recent years it is rapidly increasing.
DCASE also provides different types of competition for the submission of several papers to …