A convolutional neural network (CNN) is one of the most significant networks in the deep
learning field. Since CNN made impressive achievements in many areas, including but not …

Following their success in Computer Vision and other areas, deep learning techniques have
recently become widely adopted in Music Information Retrieval (MIR) research. However …

While deep learning has enabled great advances in many areas of music, labeled music
datasets remain especially hard, expensive, and time-consuming to create. In this work, we …

In this paper, we present madmom, an open-source audio processing and music information
retrieval (MIR) library written in Python. madmom features a concise, NumPy-compatible …

Deep neural networks have become an indispensable technique for audio source
separation (SS). It was recently reported that a variant of CNN architecture called MM …

This paper deals with the problem of audio source separation. To handle the complex and ill-
posed nature of the problems of audio source separation, the current state-of-the-art …

Deep learning techniques have been used recently to tackle the audio source separation
problem. In this work, we propose to use deep fully convolutional denoising autoencoders …

Lyrics are the words that make up a song, while chords are harmonic sets of multiple notes
in music. Lyrics and chords are generally essential information in music, ie unaccompanied …

Musical harmony analysis is usually a process of unfolding and interpreting the hierarchical
structure of music. Computational approaches to such structural analysis are still …

Self-supervised learning, especially contrastive learning, has made an outstanding
contribution to the development of many deep learning research fields. Recently …