Most existing datasets for sound event recognition (SER) are relatively small and/or domain-
specific, with the exception of AudioSet, based on over 2 M tracks from YouTube videos and …

Music source separation is the task of decomposing music into its constitutive components,
eg, yielding separated stems for the vocals, bass, and drums. Such a separation has many …

We demonstrate that language models pre-trained on codified (discretely-encoded) music
audio learn representations that are useful for downstream MIR tasks. Specifically, we …

Context: In scientific software, the inability to reproduce results is often due to technical
issues and challenges in recreating the full computational workflow from the original …

Bioacoustic sensors, sometimes known as autonomous recording units (ARUs), can record
sounds of wildlife over long periods of time in scalable and minimally invasive ways …

This paper provides a guide through the FMP notebooks, a comprehensive collection of
educational material for teaching and learning fundamentals of music processing (FMP) with …

In this artaicle, we illustrate how music may serve as a vehicle to support education in signal
processing. Using Fourier analysis as a concrete example, we demonstrate how the music …

There are a number of efforts in the MIR community towards increased reproducibility, such
as creating more open datasets, publishing code, and the use of common software libraries …

Given a music recording, music structure analysis aims at identifying important structural
elements and segmenting the recording according to these elements. In jazz music, a …

Music Information Retrieval (MIR) research is increasingly leveraging representation
learning to obtain more compact, powerful music audio representations for various …