2018-01-26 status

Done

Model Building

• Refactored Python algorithm ("Dactyler") architecture.
• Implemented unit test framework.
• Migrated Hart algorithm to new framework.
• Enhanced Hart model to support repeated notes with same pitch.
• Put announced ISMIR 2018 deadlines (March 23 and March 30) on NLP calendar.

Doing

1. Revamping my corpus module to deal with multiple voices and polyphony in abc/abcD input.
2. Supporting first-note fingering constraint in Hart model to enable the "auto-correcting" or "re-entrant" evaluation method suggested by CR.
3. Implementing DValuation base class to support evaluation methods.
4. Implementing DHamming edit-distance evaluation method.
5. Implementing DNatural edit-distance method.
6. Implementing DPivot edit-distance method.
7. Implementing DReEntry evaluation method.

In Scope for Semester

1. Re-implementing Parncutt model in framework. (The graph class I was using does not seem to exist in Python3, so this needs to be reworked.)
2. Debugging Dactylize 88-key circuit.
3. Collecting fingering data from JB performances in Elizabethtown.
4. Implementing Sayegh model.
5. Completing Dactylize II circuit.
6. Developing method to align performance data with symbolic data. I think this is going to be essential if we are to use Dactylize data moving forward and a key part of its proof of concept. I plan to have something for this at the ISMIR demo session (September 22 deadline).
7. Creating abcD for complete Beringer corpus.
8. Moving Beringer corpus to MySQL database.
9. Enhancing Parncutt, following published techniques and pushing beyond them.
10. Defining procedure for sanity test of production automatic data collector (including Beringer data).
11. Defining corpora for Dactylize data collection (WTC, Beringer, ??).
12. Implementing end-to-end machine learning experiment, using Beringer abcD data.
13. Submitting papers to ISMIR 2018. Abstracts due March 23. Papers due March 30. Ideas: a follow-up demo paper describing Dactylize data collected; a full-length paper describing application of evaluation method to models developed; a full-length description of enhanced and/or novel models, demo of method to align collected performance data with symbolic score.

Struggling

1. music21 support for abc is either buggy, or I can't read. Having a hard time splitting an abc file into right- and left-hand parts, something that should be trivial.
2. The Parncutt code is a disaster under Python 3. Lot of rework needed here.
3. Contemplating using Hart as one of the two proof-of-concept models for the methodology paper. I might even be planning on it at this point.