Usage of Unmanned Aerial Vehicles (UAVs) is growing rapidly in a wide range of consumer
applications, as they prove to be both autonomous and flexible in a variety of environments …

Automated audio captioning is a cross-modal translation task that aims to generate natural
language descriptions for given audio clips. This task has received increasing attention with …

The advancement of audio-language (AL) multimodal learning tasks has been significant in
recent years, yet the limited size of existing audio-language datasets poses challenges for …

DCASE 2017 Challenge consists of four tasks: acoustic scene classification, detection of
rare sound events, sound event detection in real-life audio, and large-scale weakly …

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

In this paper, we present a gated convolutional neural network and a temporal attention-
based localization method for audio classification, which won the 1st place in the large-scale …

Even in the absence of any explicit semantic annotation, vast collections of audio recordings
provide valuable information for learning the categorical structure of sounds. We consider …

This paper investigates the Audio Set classification. Audio Set is a large scale weakly
labelled dataset (WLD) of audio clips. In WLD only the presence of a label is known, without …

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 …

Environmental audio tagging is a newly proposed task to predict the presence or absence of
a specific audio event in a chunk. Deep neural network (DNN) based methods have been …