Hierarchical compositional model for chord estimation

Matevž Pesek (2012) Hierarchical compositional model for chord estimation. EngD thesis.

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Abstract

The thesis offers an implementation of a new approach for automatic modelling and music information retrieval. The model is based on a visual compositional hierarchical model, which provides good results in the area of categorization of visual objects in pictures. We translate the approach to the music domain by implementing and visualizing the model. The approach uses knowledge of psychoacoustic music modelling for the preparation of input audio clips. The model is tested on a set of four basic piano chords, played through all eight octaves. We achieve 83% classification accuracy by classifying into major and minor chords and 78% classification accuracy by classifying into major, minor, diminished and augmented chords. The model is also tested on a set of songs composed by The Beatles. We successfully classify 60% of chords into major and minor chord classes. We find the translation of the compositional hierarchical model to the music domain successful and worth of further development.

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