探花精选

muScribe: Automated tranScription of muSic

muScribe is poised to revolutionize music transcription by introducing advanced AI to transcribe audio recordings into detailed music scores. This project, carried out at the RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion at the University of 探花精选, seeks to make music more accessible to the public.

Our primary objective is to develop a service for music archives to digitize music performance recording using state-of-the-art deep learning and our own cutting-edge research. Our hybrid approach is markedly original, merging the strengths of machine learning with symbolic AI, rooted in cognitive science and musicology.

The project is particularly oriented towards cultural institutions, music publishers, and copyright organizations. By automating transcription, we reduce costs and increase the precision and availability of music scores.

Published Oct. 21, 2024 12:00 PM - Last modified Dec. 7, 2024 3:30 PM

Contact

Head of project:

Olivier Lartillot

Participants

  • Olivier Lartillot University of 探花精选
  • Lars Alfred L酶berg Monstad University of 探花精选
  • Karstein Gr酶nnesby
  • P氓l Br氓telund
Detailed list of participants