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 …

Research in sound classification and recognition is rapidly advancing in the field of pattern
recognition. One important area in this field is environmental sound recognition, whether it …

Anomaly-detection methods based on classification confidence are applied to the DCASE
2020 Task 2 Challenge on Unsupervised Detection of Anomalous Sounds for Machine …

Recently, a variety of acoustic tasks and related applications arised. For many acoustic
tasks, the labeled data size may be limited. To handle this problem, we propose an …

Artificial Intelligence in combination with the Internet of Medical Things enables remote
healthcare services through networks of environmental and/or personal sensors. We present …

This paper proposes sound event localization and detection methods from multichannel
recording. The proposed system is based on two Convolutional Recurrent Neural Networks …

The single recent focus on deep learning accuracy ignores economic, and environmental
cost. Progress towards Green AI is hindered by lack of universal metrics that equally reward …

In this paper, we investigate the performance of two deep learning paradigms for the audio-
based tasks of acoustic scene, environmental sound and domestic activity classification. In …

Featured Application The algorithms explored in this research can be used for any multi-
level classification applications. Abstract Recent methodologies for audio classification …

Current methodologies explored for audio classification, particularly multi-channel audio,
commonly involve the use of individual deep learning approaches. In this paper, we look at …