Data Knot – Machine Learning tools for low latency real-time performance
I am excited to finally release Data Knot, a package for Max based on FluCoMa. It’s something I’ve been developing over the last 5 years or so, the last 3 of which were under the name SP-Tools.
Data Knot is a set of machine learning tools that are optimized for low latency and real-time performance. The tools can be used with any type of audio input, including optimizations for Sensory Percussion sensors and ordinary drum triggers.
It is made up of over 120 objects actress 13 categories spanning low latency onset detection, onset-based and real-time descriptor analysis, classification and clustering, regression and prediction, corpus analysis and querying, synthesis and modeling, audio, data, and CV processing, and a slew of other abstractions that are optimized for low latency applications.
In addition to all the new updates (which you can see a detailed break down in the What’s New in v1.0 video), the update comes with six dedicated tutorial videos covering Onset Detection, Descriptors, Creating a Corpus, Classification, Regression, and how to use Sensory Percussion with Data Knot.
You can download the current version on the Max Package manager or follow the project on GitHub.
You can join the Data Knot Discord server to keep up on future updates/news as well as make suggestions, share corpora and musical examples etc…