Opendata, web and dolomites


Automatic music transcription of polyphonic audio

Total Cost €


EC-Contrib. €






Project "DoReMIR" data sheet

The following table provides information about the project.


Organization address
address: TEGNERGATAN 15
postcode: 111 40
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Sweden [SE]
 Project website
 Total cost 2˙980˙375 €
 EC max contribution 2˙086˙262 € (70%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
2. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
 Code Call H2020-SMEINST-2-2014
 Funding Scheme SME-2
 Starting year 2015
 Duration (year-month-day) from 2015-04-01   to  2017-09-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    DOREMIR MUSIC RESEARCH AB SE (STOCKHOLM) coordinator 2˙086˙262.00


 Project 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.


List of deliverables.
X-Score Challenge report Documents, reports 2019-05-30 12:45:50
API repository II Demonstrators, pilots, prototypes 2019-05-30 12:45:38
Documentation Documents, reports 2019-05-30 12:45:43
External project website Websites, patent fillings, videos etc. 2019-05-30 12:45:38
Full-scale test report Documents, reports 2019-05-30 12:45:34
X-Score Contest report Websites, patent fillings, videos etc. 2019-05-30 12:45:42
Final application iteration Demonstrators, pilots, prototypes 2019-05-30 12:45:42
New pedagogical models Documents, reports 2019-05-30 12:45:28
Cross platform selection report Documents, reports 2019-05-30 12:45:40
Final iteration of the AMT engine Demonstrators, pilots, prototypes 2019-05-30 12:45:37
Dissemination report Documents, reports 2019-05-30 12:45:37
API repository I Demonstrators, pilots, prototypes 2019-05-30 12:45:28
Ecosystem report Documents, reports 2019-05-30 12:45:41

Take a look to the deliverables list in detail:  detailed list of DoReMIR deliverables.

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The information about "DOREMIR" are provided by the European Opendata Portal: CORDIS opendata.

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