Before release: DQA of the released data!

[JamesOwers]

We should do some data quality analysis of the data we are going to release. I'm thinking a notebook (also doubles as an intro to what data are available for use) which reviews the data by:

• Playing a selection of degraded and clean excerpts
  • Any issues with data? Choppy? Did flattening tracks work well?
  • Are degradations obvious? Are there better parameters for degradations to use?
• providing stats about number of notes in those excerpts, lengths of notes, and the actual amount of time these notes occur in etc.
  • This will inform the correct seq_len to use for models (may be worth excluding silly long excerpts)
• giving some background as to where these data are from and, if possible, some summary stats about genre, or tempo, or whatever we can glean
• Summarise performance broken doWn over datasets (info available in metadata)

Essentially I want to check that the data are not rubbish, and we can hear where the degradations are!

[apmcleod]

Make sure to check for very short note (that may have been introduced by overlap checks).

[JamesOwers]

I think it will be best to add this as a notebook to the ACME repo too. Keeping issue here. Do this in conjunction with #129

[apmcleod]

Can be closed.

[JamesOwers]

Actually, I'd like to keep this. I've done some basic looks at the data, but haven't addressed specific things in the description.