Intelligent audio and music editing with deep learning

This project aims to seek novel ways of interacting with audio in music production, particularly in recording or post-production editing of multitrack audio. Recent advancements in audio analysis using deep learning enables accurate recognition and labelling of sound events in audio recordings. Labels could mark for instance musical notes, chords or other artefacts in audio recordings, and include higher level semantic annotations corresponding to temporal aspects of music such as beats or structural boundaries. These annotations present an opportunity to enhance and ease the audio editing workflow, by viewing, navigating, editing or otherwise manipulating audio recordings in novel ways, and by going beyond waveform display and manual methods of splicing and editing audio in digital audio workstations