Rare event prediction involves identifying and forecasting events with a low probability using
machine learning (ML) and data analysis. Due to the imbalanced data distributions, where …

Automatic detection and classification of animal sounds has many applications in
biodiversity monitoring and animal behavior. In the past twenty years, the volume of digitised …

Internet of Things (IoT) networks are often subject to many malicious attacks in untrusted
environments, and automatic modulation classification (AMC) is an effective way to combat …

Within a single speech emotion corpus, deep neural networks have shown decent
performance in speech emotion recognition. However, the performance of the emotion …

The prediction performance of most data-driven remaining useful life (RUL) prediction
methods relies on sufficient training samples, which is challenging in few-shot scenarios …

Mobile crowd sensing and computing (MCSC) has become a hot research area in recent
years. This article presents our vision of the next generation of MCSC, crowd intelligence …

In this paper, we study zero-shot learning in audio classification via semantic embeddings
extracted from textual labels and sentence descriptions of sound classes. Our goal is to …

Deep learning work on musical instrument recognition has generally focused on instrument
classes for which we have abundant data. In this work, we exploit hierarchical relationships …

This work addresses the problem of 3D-localizing and enhancing the speech of one main
speaker in noisy multi-speaker hospital environments using a multi-channel microphone …

Recent advances have enabled automatic sound recognition systems for deaf and hard of
hearing (DHH) users on mobile devices. However, these tools use pre-trained, generic …