Releases: polifonia-project/folk_ngram_analysis
FoNN v2.0.1
FoNN (Folk N-gram aNalysis) v2.0 contains a set of tools to ingest, preprocess and query music corpora for inter-opus similarity using three newly-developed music similarity metrics, all of which are based on local musical feature patterns extracted from digital scores. It also provides sample music corpora and ground-truth annotations to allow measurement and analysis of the performance of the bundled similarity tools, and for similar re-use in other studies. These tools have been developed with a particular focus on European musical heritage but can be applied to any machine-readable music score inputs in compatible formats (MIDI, ABC, **kern, MusicXML, and any other formats compatible with the music21 Python library).
(1) FoNN: Toolkit which uses n-gram patterns, pattern frequency and TF-IDF values, and a variety of standard and customised edit distance metrics to detect inter-opus melodic similarity. Some of FoNN's functionality has been tailored to the study of monophonic Irish & European folk music inputs but it can be applied to 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 as component is a small sample corpus for demonstration purposes, 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: Experimental work 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.
(4) Ground truth annotations: New in v2.0, this component comprises tune family ground truth annotations for a subset of 314 tunes within The Session corpus, grouped into 10 tune families. This resource can facilitate the quantitative testing measurement of the performance of music similarity tools.
In addition to the inclusion of the new component (4), this release includes a refactored and expanded version of component (1), which been re-engineered, significantly boosting both results accuracy and computational performance. Flow control, docs, and demos for component (1) have also been refactored and revised.
Full Changelog: v2.0...v2.0.1
FoNN v2.0
FoNN (Folk N-gram aNalysis) v2.0 contains a set of tools to ingest, preprocess and query music corpora for inter-opus similarity using three newly-developed music similarity metrics, all of which are based on local musical feature patterns extracted from digital scores. It also provides sample music corpora and ground-truth annotations to allow measurement and analysis of the performance of the bundled similarity tools, and for similar re-use in other studies. These tools have been developed with a particular focus on European musical heritage but can be applied to any machine-readable music score inputs in compatible formats (MIDI, ABC, **kern, MusicXML, and any other formats compatible with the music21 Python library).
(1) FoNN: Toolkit which uses n-gram patterns, pattern frequency and TF-IDF values, and a variety of standard and customised edit distance metrics to detect inter-opus melodic similarity. Some of FoNN's functionality has been tailored to the study of monophonic Irish & European folk music inputs but it can be applied to 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 as component is a small sample corpus for demonstration purposes, 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: Experimental work 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.
(4) Ground truth annotations: New in v2.0, this component comprises tune family ground truth annotations for a subset of 314 tunes within The Session corpus, grouped into 10 tune families. This resource can facilitate the quantitative testing measurement of the performance of music similarity tools.
In addition to the inclusion of the new component (4), this release includes a refactored and expanded version of component (1), which been re-engineered, significantly boosting both results accuracy and computational performance. Flow control, docs, and demos for component (1) have also been refactored and revised.
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).
FONN v0.7.0.1
PATCH: contains updates to v0.7 README.md files
FONN (FOlk N-gram aNalysis) v0.5dev 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 Damerau-Levenshtein edit distance to detect similarity between monophonic Irish folk tunes.
(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 version of component (1), now with the capacity to ingest music in ABC Notation in addition to MIDI.
It also includes an updated version of component (2), along with an expanded and improved version of component (3).
FONN v0.7dev
FONN (FOlk N-gram aNalysis) v0.5dev 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 Damerau-Levenshtein edit distance to detect similarity between monophonic Irish folk tunes.
(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 version of component (1), now with the capacity to ingest music in ABC Notation in addition to MIDI.
It also includes an updated version of component (2), along with an expanded and improved version of component (3).
FONN v0.4-dev
FONN (FOlk N-gram aNalysis) repo 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:
FONN: Work-in-progress on tools that make use of n-grams and Damerau-Levenshtein edit distance to explore melodic similarity between monophonic Irish folk tunes.
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.
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.
FONN v0.3-dev
FONN (FOlk N-gram aNalysis) repo 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:
- FONN: Work-in-progress on tools that make use of n-grams and Damerau-Levenshtein edit distance to explore melodic similarity between monophonic Irish folk tunes.
- 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.
- 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.
FONN v0.2-dev
FONN (FOlk N-gram aNalysis) repo 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:
- FONN: Work-in-progress on tools that make use of n-grams and Damerau-Levenshtein edit distance to explore melodic similarity between monophonic Irish folk tunes.
- 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.
- Root Key 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.