Automatic transcription of polyphonic music to a correct music notation is considered to be the ´holy grail´ of music analysis with important implications for music education, music creation and the preservation of music.

This interdisciplinary project, combining advanced methods in signal analysis with the most advanced analytical methods in music cognition, involves a new approach to solve this problem.

In addition to a technical solution for the problem above, we will develop applications and methods for music education and creation with leading European music educators.

One of the integrations of this new technology will be into DoReMIRs new ScoreCloud product suite:

The project’s objectives have been structured in 4 key areas that define clear, measurable key performance indicators or KPIs:

Objective 1 (develop a cloud-based polyphonic music transcription solution based on new signal processing models): the project will develop a robust and accurate transcription engine able to process polyphonic music in the cloud and to provide the resulting data to any applications using its APIs.

Objective 2 (develop new tools and applications supporting new pedagogical models for music schools): the project will implement a first application example (score transcription application for music composing and music teaching).

Objective 3 (develop a vibrant ecosystem around the technology and models): the project will publish APIs and encourage third party developers to come up with their own innovative application ideas, based on the polyphonic music transcription engine.

Objective 4 (successfully translate research results in scalable technology): the project will develop all the necessary foundations for a successful exploitation (product market launch) after the end of the project.