Publications related to Harmonic Syntax in Time: Rhythm Improves Grammatical Models of Harmony

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Automating Grammar Comparison

Viktor Kuncak, Mikaël Mayer, Ravichandhran Kandhadai Madhavan

We consider from a practical perspective the problem of checking equivalence of context-free grammars. We present techniques for proving equivalence, as well as techniques for finding counter-examples that establish non-equivalence. Among the key building ...

Assoc Computing Machinery2015

Towards Automating Grammar Equivalence Checking

Viktor Kuncak, Mikaël Mayer, Ravichandhran Kandhadai Madhavan

We consider from practical perspective the (generally undecidable) problem of checking equivalence of context-free grammars. We present both techniques for proving equivalence, as well as techniques for finding counter-examples that establish non-equivalen ...

2015

Musical training intensity yields opposite effects on grey matter density in cognitive versus sensorimotor networks

Dimitri Nestor Alice Van De Ville, François Lazeyras

Using optimized voxel-based morphometry, we performed grey matter density analyses on 59 age-, sex- and intelligence-matched young adults with three distinct, progressive levels of musical training intensity or expertise. Structural brain adaptations in mu ...

Springer Heidelberg2014

Probabilistic models for music

Jean-François Paiement

This thesis proposes to analyse symbolic musical data under a statistical viewpoint, using state-of-the-art machine learning techniques. Our main argument is to show that it is possible to design generative models that are able to predict and to generate m ...

École Polytechnique Fédérale de Lausanne2008

Predictive Models for Music

Samy Bengio, Jean-François Paiement

Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce generative models for melodies. We decompose melodic ...

IDIAP2008

A Distance Model for Rhythms

Samy Bengio, Jean-François Paiement

Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce a model for rhythms based on the distributions of di ...

2008

A Distance Model for Rhythms

Samy Bengio, Jean-François Paiement

Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce a model for rhythms based on the distributions of di ...

IDIAP2008

A Generative Model for Rhythms

Samy Bengio, Jean-François Paiement

Modeling music involves capturing long-term dependencies in time series, which has proved very difficult to achieve with traditional statistical methods. The same problem occurs when only considering rhythms. In this paper, we introduce a generative model ...

2007

A Generative Model for Rhythms

Samy Bengio, Jean-François Paiement

IDIAP2007