This paper presents the Jazz Transformer, a generative model that utilizes a neural
sequence model called the Transformer-XL for modeling lead sheets of Jazz music …

Various disconnected chord datasets are currently available for music analysis and
information retrieval, but they are often limited by either their size, non-openness, lack of …

Recent advances in automatic piano transcription have enabled large scale analysis of
piano music in the symbolic domain. However, the research has largely focused on classical …

We introduce the Harmonix set: a collection of annotations of beats, downbeats, and
functional segmentation for over 900 full tracks that covers a wide range of western popular …

Deep Learning methods achieve state-of-the-art in many tasks, including vocal pitch
extraction. However, these methods rely on the availability of pitch track annotations without …

Computationally creative systems for music have recently achieved impressive results,
fuelled by progress in generative machine learning. However, black-box approaches have …

Recent work in music structure analysis has shown the potential of deep features to highlight
the underlying structure of music audio signals. Despite promising results achieved by such …

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 …

The practices of data collection in training sets for Automatic Music Generation (AMG) tasks
are opaque and overlooked. In this paper, we aimed to identify these practices and surface …

We propose a system for tracking beats and downbeats with two objectives: generality
across a diverse music range, and high accuracy. We achieve generality by training on …