Music signal processing may appear to be the junior relation of the large and mature field of
speech signal processing, not least because many techniques and representations …

In this paper we present Aligned Scores and Performances (ASAP): a new dataset of 222
digital musical scores aligned with 1068 performances (more than 92 hours) of Western …

In this paper, we propose a method that can identify challenging music samples for beat
tracking without ground truth. Our method, motivated by the machine learning method …

We introduce a method for imposing higher-level structure on generated, polyphonic music.
A Convolutional Restricted Boltzmann Machine (C-RBM) as a generative model is combined …

Algorithms for musical tempo estimation have become increasingly complicated in recent
years. These algorithms typically utilize two fundamental properties of musical rhythm: some …

A new probabilistic framework for beat tracking of musical audio is presented. The method
estimates the time between consecutive beat events and exploits both beat and non-beat …

We present a methodology for the real time alignment of music signals using sequential
Monte Carlo inference techniques. The alignment problem is formulated as the state tracking …

In this article, we present an extensive survey of music information retrieval (MIR) research
into music playlists. Our survey spans more than 20 years, and includes around 300 papers …

Even though local tempo estimation promises musicological insights into expressive musical
performances, it has never received as much attention in the music information retrieval …

Several MIR applications require fine-grained note alignments between MIDI performances
and their musical scores for training and evaluation. However, large and high-quality …