most citedFrom Bach to the Beatles: The simulation of human tonal expectation using ecologically-trained predictive models

7 citations · 18 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD20175 cited

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…

cs.SD20173 cited

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…

cs.SD2017

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…

cs.SD20177 cited

From Bach to the Beatles: The simulation of human tonal expectation using ecologically-trained predictive models

Carlos Cancino-Chacón, Maarten Grachten, Kat Agres

Tonal structure is in part conveyed by statistical regularities between musical events, and research has shown that computational models reflect tonal structure in music by capturi…

cs.CV20173 cited

Improving Content-Invariance in Gated Autoencoders for 2D and 3D Object Rotation

Stefan Lattner, Maarten Grachten

Content-invariance in mapping codes learned by GAEs is a useful feature for various relation learning tasks. In this paper we show that the content-invariance of mapping codes for…