Networked Remote Music Collaboration using Machine Learning

Communication using mediums like video and audio are essential for a lot of professions. In this paper, interaction with real time audio transmission is looked upon using the tools provided by the domains of IoT and Machine Learning. The transport layer protocols - TCP and UDP are examined for audio transmission quality. Further, different Recurrent Neural Networks (RNN) models are examined for their efficiency in predicting music in case of loss of packets during transmission. These predictions fill in the gaps and help prevent any lag in a real time performance/jam where the loss of musical notes can be a hindrance.