Explore the words cloud of the MIP-Frontiers project. It provides you a very rough idea of what is the project "MIP-Frontiers" about.
The following table provides information about the project.
QUEEN MARY UNIVERSITY OF LONDON
|Coordinator Country||United Kingdom [UK]|
|Total cost||3˙926˙675 €|
|EC max contribution||3˙926˙675 € (100%)|
1. H2020-EU.1.3.1. (Fostering new skills by means of excellent initial training of researchers)
|Duration (year-month-day)||from 2018-04-01 to 2022-03-31|
Take a look of project's partnership.
|1||QUEEN MARY UNIVERSITY OF LONDON||UK (LONDON)||coordinator||819˙863.00|
|2||INSTITUT MINES-TELECOM||FR (PALAISEAU)||participant||1˙051˙502.00|
|3||UNIVERSIDAD POMPEU FABRA||ES (BARCELONA)||participant||743˙618.00|
|4||UNIVERSITAT LINZ||AT (LINZ)||participant||511˙868.00|
|5||ROLI Ltd||UK (London)||participant||273˙287.00|
|6||DOREMIR MUSIC RESEARCH AB||SE (STOCKHOLM)||participant||263˙659.00|
|7||SONY EUROPE LIMITED||UK (WEYBRIDGE)||participant||262˙875.00|
|9||BMAT LICENSING SL||ES (BARCELONA)||partner||0.00|
|10||Deezer SA||FR (Paris)||partner||0.00|
|11||Eliette und Herbert von Karajan Institut||AT (Salzburg)||partner||0.00|
|12||JAMENDO SA||LU (LUXEMBOURG)||partner||0.00|
|13||NATIVE INSTRUMENTS GMBH||DE (BERLIN)||partner||0.00|
|14||Technicolor R&D France||FR (ISSY LES MOULINEAUX)||partner||0.00|
|15||Tido Enterprise GmbH||DE (London)||partner||0.00|
|16||Wiener Staatsoper GmbH||AT (Vienna)||partner||0.00|
Music Information Processing (also known as Music Information Research; MIR) involves the use of information processing methodologies to understand and model music, and to develop products and services for creation, distribution and interaction with music and music-related information. MIR has reached a state of maturity where there are standard methods for most music information processing tasks, but as these have been developed and tested on small datasets, the methods tend to be neither robust to different musical styles or use contexts, nor scalable to industrial scale datasets. To address this need, and to train a new generation of researchers who are aware of, and can tackle, these challenges, we bring together leading MIR groups and a wide range of industrial and cultural stakeholders to create a multidisciplinary, transnational and cross-sectoral European Training Network for MIR researchers, in order to contribute to Europe's leading role in this field of scientific innovation, and accelerate the impact of innovation on European products and industry.
The researchers will develop breadth in the fields that make up MIR and in transferable skills, whilst gaining deep knowledge and skills in their own area of speciality. They will learn to perform collaborative research, and to think entrepreneurially and exploit their research in new ways that benefit European industry and society.
The proposed work is structured along three research frontiers identified as requiring intensive attention and integration (data-driven, knowledge-driven, and user-driven approaches), and will be guided by and grounded in real application needs by a unique set of industrial and cultural stakeholders in the consortium, which range from consumer electronics companies and big players in media entertainment to innovative SMEs, cultural institutions, and even a famous opera house, thus encompassing a very wide spectrum of the digital music world.
|Dissemination and Public Engagement Plan||Documents, reports||2020-03-06 15:53:23|
|Summer School||Other||2020-03-06 15:53:25|
|Project Web Site and Social Media Launch||Websites, patent fillings, videos etc.||2020-03-06 15:36:16|
Take a look to the deliverables list in detail: detailed list of MIP-Frontiers deliverables.
|year||authors and title||journal||last update|
Giorgia Cantisani, Gabriel TrÃ©goat, Slim Essid, GaÃ«l Richard
MAD-EEG: an EEG dataset for decoding auditory attention to a target instrument in polyphonic music
published pages: 51-55, ISSN: , DOI: 10.21437/smm.2019-11
|SMM19, Workshop on Speech, Music and Mind 2019||2020-03-05|
Demirel, Emir; Baris Bozkurt; Serra, Xavier
Automatic chord-scale recognition using harmonic pitch class profiles
published pages: , ISSN: , DOI: 10.5281/zenodo.3249257
|16th Sound & Music Computing Conference (SMC 2019) 5||2020-03-05|
Agrawal R., and Dixon S.
A Hybrid Approach to Audio-to-Score Alignment
published pages: , ISSN: , DOI:
|36th International Conference on Machine Learning (ICML 2019),||2020-03-05|
Emir Demirel, Queen Mary University of London
Baris Bozkurt, Izmir Democracy University
Xavier Serra, Universitat Pompeu Fabra
AUTOMATIC CHORD-SCALE RECOGNITION USING HARMONIC
published pages: , ISSN: , DOI:
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The information about "MIP-FRONTIERS" are provided by the European Opendata Portal: CORDIS opendata.
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