The following code chunks print the full list of the synth defitions (SynthDef) that are loaded in the server. A Synthdef is the client side representation of a synth on the server-side. SynthDef library // print all the SynthDefs ( SynthDescLib.global.synthDescs.associationsDo { |assoc| var name = assoc.key, code = assoc.value.def.func.def.sourceCode; code.notNil.if { "".postln; name.post; ": ".postln; code.postln; }; }; ""; ) ( SynthDescLib.global.synthDescs.do { |desc| if(desc.def.notNil) { "\nSynthDef %\n".postf(desc.name.asCompileString); desc.def.func.postcs; }; }; "" // this prevents the synthDescs collection from posting )

This blog post is about machine learning techniques in live coding. I particularly focused on SuperCollider (SC3) and scikit-learn library for Python3. The main procedure was to send data over Open Sound Control (OSC) protocol, using pythonosc, and to analyze the data in Python3. The data analysis results are sending back to sclang in real-time for parameter control of UGens. Description and order of execution The main idea is to get input of environmental sounds using a microphone (also input from speakers works fine), and to analyze the input based on Chromagram class from SC3.

This blog entry provide information about the setup of a Hugo blog using orgmode. Hugo has been established in the field of static websites and blogs. It is based on Go programming language. The user is writing her posts in Markdown which makes it easy to use. I decided to quit Jekyll (and particular org2jekyll) and to begin a new blog using Hugo & orgmode. Hugo has a large collection of templates, and the present template is called hugo-dusk.