FoNN v1.0

FoNN (Folk N-gram aNalysis) v0.8 targets the identification of patterns that are useful in detecting relationships between pieces of music, with a particular focus on European musical heritage. At present, it includes three components:

(1) FoNN: Toolkit which uses n-grams and Levenshtein edit distance to detect inter-opus melodic similarity. Some FoNN's functionality is tailored for Irish and related folk music inputs but it can be used on any music corpus in a compatible symbolic notation format.
FoNN includes ingest pipeline tools for creation of Knowledge Graphs from music corpus data via the Polifonia Patterns Knowledge Graph repo.
Also included with this component are two test corpora: The Session corpus of Irish traditional tunes and The Meertens Tune Collection Annotated Corpus (MTC-ANN) of Dutch folk songs.

(2) Ceol Rince na hÉireann (CRÉ) corpus: A cleaned and annotated version of the Ceol Rince na hÉireann corpus of Irish traditional dance music, containing 1,224 monophonic MIDI files, and a csv table of root note values for each file.

(3) Root Note Detection: Work in progress on development of a Machine Learning-based root note detection algorithm, exploring the use of decision tree and random forest techniques to aggregate and improve the accuracy of an ensemble of root detection metrics.

This release includes a refactored and expanded version of component (1).