A probabilistic model for melodies Jean-François Paiement Yahoo! Labs In this presentation, I will describe a generative model for melodies in a given musical genre, using symbolic representation of musical data. Our first contribution is to specify melodic features based on musicological substantiation that represent the plausibility of sequences of three consecutive notes. Their probabilistic modeling is an interesting intermediate problem because the cardinality of such features is much lower than the number of sequences of three notes. I will then introduce a probabilistic model of melodies given chords and rhythms based on these features. This model leads to significantly higher prediction performances than a simpler Input/Output Hidden Markov Model. Moreover, sampling this model given appropriate musical contexts generates realistic melodies. Audio examples of the melodies generated by the models will be played through the talk.