Objective
DoReMIR Music Research has already launched several successful products for music analysis and composition and has a large user base of monophonic audio analysis worldwide. The project builds on and extends a product suite called ScoreCloud with the focus on easy creation and distribution of music notation. The ScoreCloud concept is technically built on mobile and desktop apps connected with a full cloud based back-end. The product enables users to notate music directly from performance: a Google Translate for Music!
The project will develop a low-cost, cloud-based, polyphonic audio transcription solution based on an interdisciplinary approach (musicology, acoustics, audio engineering, cognitive science and computing) and a user-driven design (agile iterative solution development with end-user participation in the context of music teaching and music composition).
In order to circumvent the limitations of current automated transcription methods, the project uses a novel approach to musical and music signal analysis, by modelling and using high-level musical knowledge (about stylistic conventions, music cognition, etc.) and machine learning techniques. In addition to finding better solutions to certain analysis problems, the resulting systems will also be able to communicate their results in musically meaningful, high-level terms.
Fields of science
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsignal processing
- natural sciencesphysical sciencesacoustics
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- humanitiesartsmusicology
- social sciencespsychologycognitive psychology
Programme(s)
Funding Scheme
SME-2 - SME instrument phase 2Coordinator
111 40 STOCKHOLM
Sweden
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.