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# Features
* RTNeural support. Should probably be a separate library or an optional dependency.
- This is important to justify the thesis as related to AI.
Since it is a C++ library making extensive use of templates, there will have to be
a small C wrapper.
Since build time options are important (to choose the backend), it will have to be
@@ -70,6 +69,12 @@
* Spectrogram output via ffmpeg.
This can be made to work in a window, Jupyter notebook and in the console.
Theoretically, we can even support realtime analysis and render into Kitty by piping into mpv.
+* Built-in tracker-like sequencer, ie. stream compiler.
+ Will read a simple DSL where each tab corresponds to an output stream.
+ Rows will be triggered in a given tempo. In each cell, you can place a MIDI note name
+ or directly a number.
+ The result is an automatic note-on/off signal. This wouldn't be compatible with Stream:mvelocity(),
+ though.
* Unit Tests.
We could use LuaUnit (https://github.com/bluebird75/luaunit) and directly import luaunit.lua
or add a Git submodule.