Evaluating language models of tonal harmony

David R.W. Sears, Filip Korzeniowski, Gerhard Widmer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This study borrows and extends probabilistic language models from natural language processing to discover the syntactic properties of tonal harmony. Language models come in many shapes and sizes, but their central purpose is always the same: to predict the next event in a sequence of letters, words, notes, or chords. However, few studies employing such models have evaluated the most state-of-the-art architectures using a large-scale corpus of Western tonal music, instead preferring to use relatively small datasets containing chord annotations from contemporary genres like jazz, pop, and rock. Using symbolic representations of prominent instrumental genres from the common-practice period, this study applies a flexible, data-driven encoding scheme to (1) evaluate Finite Context (or n-gram) models and Recurrent Neural Networks (RNNs) in a chord prediction task; (2) compare predictive accuracy from the best-performing models for chord onsets from each of the selected datasets; and (3) explain differences between the two model architectures in a regression analysis. We find that Finite Context models using the Prediction by Partial Match (PPM) algorithm outperform RNNs, particularly for the piano datasets, with the regression model suggesting that RNNs struggle with particularly rare chord types.

Original languageEnglish
Title of host publicationProceedings of the 19th International Society for Music Information Retrieval Conference, ISMIR 2018
EditorsEmilia Gomez, Xiao Hu, Eric Humphrey, Emmanouil Benetos
PublisherInternational Society for Music Information Retrieval
Pages211-217
Number of pages7
ISBN (Electronic)9782954035123
StatePublished - 2018
Event19th International Society for Music Information Retrieval Conference, ISMIR 2018 - Paris, France
Duration: Sep 23 2018Sep 27 2018

Publication series

NameProceedings of the 19th International Society for Music Information Retrieval Conference, ISMIR 2018

Conference

Conference19th International Society for Music Information Retrieval Conference, ISMIR 2018
Country/TerritoryFrance
CityParis
Period09/23/1809/27/18

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