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 paper, we introduce a new problem, named audio-visual video parsing, which aims to
parse a video into temporal event segments and label them as either audible, visible, or …

COVID-19, otherwise known as the coronavirus, has precipitated the world into a pandemic
that has infected, as of the time of writing, more than 10 million persons worldwide and …

For intelligent systems to make best use of the audio modality, it is important that they can
recognize not just speech and music, which have been researched as specific tasks, but …

Environmental sound detection is a challenging application of machine learning because of
the noisy nature of the signal, and the small amount of (labeled) data that is typically …

This workshop paper presents our contribution for the acoustic scene classification (ASC)
task proposed for the “detection and classification of acoustic scenes and events”(DCASE) …

In this paper, we demonstrate how we applied convolutional neural network for DCASE
2017 task 1, acoustic scene classification. We propose a variety of preprocessing methods …

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 problem related to the field of machine listening
whose objective is to classify/tag an audio clip in a predefined label describing a scene …

ABSTRACT This paper proposes Convolutional Neural Network (CNN) ensembles for
acoustic scene classification of tasks 1A and 1B of the DCASE 2018 challenge. We …