Demonstation video belonging to the paper “Pattern-Based Music Generation with Wasserstein Autoencoders and PR^c Descriptions” by Tijn Borghuis, Luca Angioloni, Lorenzo Brusci and Paolo Frasconi.
We put together a series of questions raised by our users, early adopters and other professionals in the audio-visual and music industries, and discussed them with Musico CEO Lorenzo Brusci and other members of the technical team. The result is a fascinating conversation about the role of music and AI in the upcoming years, across […]
Simpifying the access and usability of machine learning-based music generations: AI content generation usability is not a simple task. See how we have been coupling with the topic in our LIVE AI channel. https://www.musi-co.com/listen/live The organisation of music tasks, based on consolidated DAW management procedures is one (revolutionary) thing. Embedding instant music behaviours, assuming the […]
Check out our paper on “ImproBEAT”, our full Ai drummer. Off the Beaten Track: Using Deep Learning to Interpolate Between Music Genres. abstract: We describe a system based on deep learning that generates drum patterns in the electronic dance music domain. Experimental results reveal that generated patterns can be employed to produce musically sound and […]