metiu-metiu / high-level-timbral-features-extractor

Convolutional-based supervised regression task for extracting high level timbral features from drums sound files, useful to condition a real time Neural Sound Synthesiser on continuous intuitive controls.

Extremely dedicated and passioned Musician and Audio/Music Software Engineer specialised in Neural Sound Synthesis and Music Composition.

I acquired a multidisciplinary expertise about the Art of Music and the Science and Technology of Sound; I am deeply interested in Generative AI for Music and Sound Design, and any Machine Learning Software dedicated to foster people’s creativity.

Sound and Music Computing Master (UPF, Barcelona) graduate, with a Thesis Project on Real-time Neural Texture Sound Synthesis exposing physically-driven continuous controls with synthetic-to-real Unsupervised Domain Adaptation, supervised by Lonce Wyse.

Some of my recent works: https://github.com/Metiu-Metiu?tab=repositories

My CV: https://www.linkedin.com/in/matteo-fabbri-684988131/

Proficient in JUCE, C++, Python, Pytorch.

Currently looking for new professional opportunities.