221 citations · 1k across the 103 of their papers we have counts for
15 papers · 1 filter
The ACCompanion v0.1: An Expressive Accompaniment System
Carlos Cancino-Chacón, Martin Bonev, Amaury Durand +5
In this paper we present a preliminary version of the ACCompanion, an expressive accompaniment system for MIDI input. The system uses a probabilistic monophonic score follower to t…
Deep Within-Class Covariance Analysis for Robust Audio Representation Learning
Hamid Eghbal-zadeh, Matthias Dorfer, Gerhard Widmer
Convolutional Neural Networks (CNNs) can learn effective features, though have been shown to suffer from a performance drop when the distribution of the data changes from training…
What were you expecting? Using Expectancy Features to Predict Expressive Performances of Classical Piano Music
Carlos Cancino-Chacón, Maarten Grachten, David R. W. Sears +1
In this paper we present preliminary work examining the relationship between the formation of expectations and the realization of musical performances, paying particular attention…
Learning Musical Relations using Gated Autoencoders
Stefan Lattner, Maarten Grachten, Gerhard Widmer
Music is usually highly structured and it is still an open question how to design models which can successfully learn to recognize and represent musical structure. A fundamental pr…
Probabilistic Generative Adversarial Networks
Hamid Eghbal-zadeh, Gerhard Widmer
We introduce the Probabilistic Generative Adversarial Network (PGAN), a new GAN variant based on a new kind of objective function. The central idea is to integrate a probabilistic…
Piece Identification in Classical Piano Music Without Reference Scores
Andreas Arzt, Gerhard Widmer
In this paper we describe an approach to identify the name of a piece of piano music, based on a short audio excerpt of a performance. Given only a description of the pieces in tex…