Modeling Melodic Improvisation in Turkish Folk Music Using Variable-Length Markov Models

Computational Modeling of Improvisation in Turkish Folk Music Using Variable-length Markov Models

The paper describes a new database, which currently consists of 64 songs encompassing approximately 6600 notes, and a system, which uses Variable-Length Markov Models (VLMM) to predict the melodies in the uzun hava (long tune) form, a melodic structure in Turkish folk music. The work shows VLMMs are highly predictive. This suggests that variable-length Markov models (VLMMs) may be applied to ma...

Multiple Viewpoint Modeling of North Indian Classical Vocal Compositions

Previous research has shown that ensembles of variable length Markov models (VLMMs), known as Multiple Viewpoint Models (MVMs), can be used to predict the continuation of Western tonal melodies, and outperform simpler, fixed-order Markov models. Here we show that this technique can be effectively applied to predicting melodic continuation in North Indian classical music, providing further evide...

Comparing Probabilistic Models for Melodic Sequences

Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre. We perform a comparative analysis of two probabilistic models; a Dirichlet Variable Length Markov Model (Dirichlet-VMM) and a Time Convolutional Restricted Boltzmann Machine (TC-RBM). We show that the TC-RBM learns descriptive music featu...

N-gram Modeling of Tabla Sequences Using Variable-length Hidden Markov Models for Improvisation and Composition

Probabilistic models for melodic prediction

Chord progressions are the building blocks from which tonal music is constructed. The choice of a particular representation for chords has a strong impact on statistical modeling of the dependence between chord symbols and the actual sequences of notes in polyphonic music. Melodic prediction is used in this paper as a benchmark task to evaluate the quality of four chord representations using tw...