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

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 …

Music information retrieval (MIR) is a fast-growing research area. One of its aims is to extract
musical characteristics from audio. In this study, we assumed the roles of researchers …

We explore frame-level audio feature learning for chord recognition using artificial neural
networks. We present the argument that chroma vectors potentially hold enough information …

We propose a multi-task learning approach for simultaneous tempo estimation and beat
tracking of musical audio. The system shows state-of-the-art performance for both tasks on a …

We present a single-step musical tempo estimation system based solely on a convolutional
neural network (CNN). Contrary to existing systems, which typically first identify onsets or …

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 …

Many researchers use convolutional neural networks with small rectangular filters for music
(spectrograms) classification. First, we discuss why there is no reason to use this filters setup …

Music similarity search is useful for a variety of creative tasks such as replacing one music
recording with another recording with a similar" feel", a common task in video editing. For …

Metric learning for music is an important problem for many music information retrieval (MIR)
applications such as music generation, analysis, retrieval, classification and …