: Send audio from a digital audio workstation (DAW) to a remote room for a singer or producer to listen in real-time.
ROC Toolkit is an open-source, distributed data processing framework designed to handle large-scale data processing workloads. It was initially developed by a team of researchers at the University of California, Berkeley, and is now maintained by a community of contributors. ROC's primary goal is to provide a resilient and efficient data processing framework that can handle the demands of modern data-intensive applications.
Most classifiers (logistic regression, random forests, neural networks) output a probability between 0 and 1. By default, we use a 0.5 threshold: predict "1" if probability > 0.5, else "0". But this threshold is arbitrary.
It’s widely used in .
: Uses Forward Erasure Correction (FEC) codes to restore packets lost during transmission.
: Automatically converts between sender and receiver clock domains to prevent audio drift.