2018-07-19 status

Done

Administrivia

1. Booked trip to ISMIR 2018 in Paris.

Model Building

1. Finailized "Corrected Parncutt" implementation for everything by cyclic patterns.
2. Confirmed inconsistencies in published Parncutt results:
• Small-Span and Large-Span penalties are conflated.
• Small-Span penalty definition is inconsistent.
• Position-Change-Count and Position-Change-Size penalties are incorrect.
• Penalty totals are incorrect.
• Explanatory example has confusing/incorrect costs.
3. Completed full regression test of code base.
4. Met with Alex Demos and agreed to co-author paper for Music Scientiae on Parncutt, Corrected Parncutt, Improved Parncutt, and how to tell them apart. Will dry run some of this material in late-breaking paper at ISMIR.

Doing

1. Implementing support for, and clarifying definition of, cyclic pattern constraint in Parncutt. (Should also do this for Sayegh and Hart.)
2. Double-checking pruning mechanism in Parncutt.
3. Writing up findings on "Corrected Parncutt" model, initially for ISMIR submission.
4. Adding mechanism to learn weights for "Improved Parncutt" rules from training data.

Struggling

1. How does one compare two ranked lists of sequences to a third and claim one of the two is more similar to the third in a statistically significant way? That is the big question.

In Scope

1. Implementing crude automatic segmenter.
2. Developing staccato/legato classifier.
3. Demonstrating improved Parncutt via #1 and #2.
4. Debugging Sayegh model, which produces results inconsistent with training data.
5. Developing better test cases for Sayegh.
6. Updating abcDE to support manual segmentation.
7. Completing and polishing abcD for entire Beringer corpus.
8. Defining initial benchmark corpora and evaluation methodology.
9. Implementing convenience methods for reporting benchmark results.
10. Moving Beringer corpus to MySQL database.
11. Enhancing Parncutt, following published techniques and pushing beyond them.
12. Enhancing Hart and Sayegh to return top n solutions.
13. Re-weighting Parncutt rules using machine learning and TensorFlow. (This seems like a good fit.)
14. Adding support to abcDE for annotating phrase segmentation.
15. Debugging Dactylize 88-key circuit.
16. Collecting fingering data from JB performances in Elizabethtown.
17. Completing Dactylize II circuit.
18. 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).
19. Defining procedure for sanity test of production automatic data collector (including Beringer data).
20. Defining corpora for Dactylize data collection (WTC, Beringer, ??).
21. Implementing end-to-end machine learning experiment, using Beringer abcD data.
22. Submitting papers to TISMIR. 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.