Acoustic scene classification (ASC) has gained significant interest recently due to its diverse
applications. Various audio signal processing and machine learning methods have been …

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 …

In this article, we present an account of the state of the art in acoustic scene classification
(ASC), the task of classifying environments from the sounds they produce. Starting from a …

The aim of this paper is to investigate the feasibility of an audio-based context recognition
system. Here, context recognition refers to the automatic classification of the context or an …

Mobile workers need seamless access to communication and information services while on
the move. However, current solutions overwhelm users with intrusive interfaces and …

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 …

Acoustic Scene Classification (ASC) is a task that classifies a scene according to
environmental acoustic signals. Audios collected from different cities and devices often …

Human activity recognition is crucial for a better understanding of workers in construction
sites and people in the built environment. Previous studies have been proposed various …

The acoustic environment provides a rich source of information on the types of activity,
communication modes, and people involved in many situations. It can be accurately …

In the context of the Internet of Things, sound sensing applications are required to run on
embedded platforms where notions of product pricing and form factor impose hard …