In this paper, we study the performance of variants of well-known Convolutional Neural
Network (CNN) architectures on different audio tasks. We show that tuning the Receptive …

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 …

While the automatic recognition of musical instruments has seen significant progress, the
task is still considered hard for music featuring multiple instruments as opposed to single …

This paper introduces OrchideaSOL, a free dataset of samples of extended instrumental
playing techniques, designed to be used as default dataset for the Orchidea framework for …

Current music emotion recognition (MER) systems rely on emotion data averaged across
listeners and over time to infer the emotion expressed by a musical piece, often neglecting …

Small adversarial perturbations of input data can drastically change the performance of
machine learning systems, thereby challenging their validity. We compare several …

Identification of musical instruments is a vital problem in the area of Music Information
Retrieval. Automatic music classification provides the foundation for a variety of advanced AI …

HuQin is a family of traditional Chinese bowed string instruments. Playing techniques (PTs)
embodied in various playing styles add abundant emotional coloring and aesthetic feelings …

Machine learning techniques have proved useful for classifying and analyzing audio
content. However, recent methods typically rely on abstract and high-dimensional …

Vibratos, tremolos, trills, and flutter-tongue are techniques frequently found in vocal and
instrumental music. A common feature of these techniques is the periodic modulation in the …