---
# System prepended metadata

title: 1201 meeting note
tags: [meeting note]

---

# 1201 meeting note
###### tags: `meeting note`

- tasks
  1. define input
     - derive from other instruments midi
       - [chromagram](https://en.wikipedia.org/wiki/Chroma_feature) of melodic instruments
         - https://craffel.github.io/pretty-midi/#pretty_midi.PrettyMIDI.get_chroma
       - drum pattern or other instruments’ onsets
     - speed, number of instrument, time signature, beat position
     - other infos
       - style, rhythm type, composer, etc.
       - need to find other source for these info
         - [kaggle jazz-standard](https://www.kaggle.com/datasets/melihcanyardi/jazz-standards)
         - [JSD dataset](https://jazzomat.hfm-weimar.de/dbformat/synopsis/solo1.html)
     - input format
       - chromagram 12x3
       - speed (int)
       - number of instrument (int)
       - time signature (2 int)
       - beat position (int)
       - bar position (int)
       - ![](https://i.imgur.com/487zchT.png)
  2. define output
     - one input per bar, one output per bar (one to one)
       - (time(16th note), midi num(+rest))
     - one input per bar, one output per step(16th note) (one to many)
       - midi num(+rest)
     - one input per step, one output per step (one to one) ☑︎
       - midi num(+rest)
  ![](https://i.imgur.com/3rbum5h.png)
  3. define loss
     - octave distance
     - pitch distance
     - simple cross-entropy?
  4. find and preprocess data
     - [thejazzpage](http://www.thejazzpage.de/index1.html)
     - [minor9](https://bhs.minor9.com/midi/jazzstandards/)
     - [Doug McKenzie Jazz](http://bushgrafts.com/wp/) (some)
     - [Jazz ML ready MIDI](https://www.kaggle.com/datasets/saikayala/jazz-ml-ready-midi)
  5. build basic model
     - RNN LSTM (https://www.tensorflow.org/api_docs/python/tf/keras/layers/LSTM)
     - RNN GRU (https://www.tensorflow.org/api_docs/python/tf/keras/layers/GRU)
     - [tensorflow RNN tutorial](https://www.tensorflow.org/guide/keras/rnn)
- questions
  - solo and accompany mode?
- other data resource
  - https://github.com/wayne391/symbolic-music-datasets
  - https://fourscoreandmore.org/musoRepo/
  - https://groups.google.com/a/tensorflow.org/g/magenta-discuss/c/6ZLbzTjjpHM
- RNN in DL course
  - https://nthu-datalab.github.io/ml/#lecture12
