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Towards Richer Online Music Public-domain Archives

Deliverables

Music description

Music description [M10, M20; T3.2] Identification and implementation of multimodal music descriptors of interest for the end user pilots

Annotation tools

Annotation tools [M12; M34; T5.5] The first release will include basic annotation tasks and initial integration of crowd planning strategies. The second release will consist of a consolidated version of the first release, including additional annotation tasks.

Multimodal music information alignment

Multimodal music information alignment [M10, M24; T3.5] Selected pieces of the standard repertoire provided with temporal alignment between different modalities, including partial sources.

Project handbook

Project handbook [M3; T1.1] Including all procedures, communication channels and operational framework

Music performance assessment

Music performance assessment [M12, M34; T5.4] This deliverable will include automatic models to predict performance difficulty of (solo) instrumental scores and to rate the quality of their performance. At first, “difficulty indices” to denote performance difficulty of a given piece are specified and validated on preliminary data (e.g., solo lute and piano repertoire). Subsequently, performance quality assessment metrics involving audio and score information are developed and systematically validated via human feedback.

Annual dissemination report

Annual dissemination report [M12, 24, 36; T7.1–5] Dissemination overview and yearly plan, listing achievements per year and outlook for next year covering different stakeholders.

TROMPA processing library

TROMPA processing library [M12, M34; T5.3] This deliverable will provide a library for embeddable descriptions and synthesis of music data coming from supported music data repositories. First release: library components individually available; Second release: all library components working in sync together.

Data infrastructure

Data infrastructure [M6, M30; T5.1] Iterations of the TROMPA data infrastructure jointly built by partners in T5.1

Data resource preparation

Data resource preparation [M10, M18; T3.1] Identification and collecting of musical (multimodal) data to be exploited within TROMPA. It will consider musicological collections available for research as well as existing digital repositories relevant for the different pilots.

Develop project website and blog

Develop project website and blog [M3; T7.1-6] Project website: a multimedia website with public information on the project and its evolution. It will include a blog to achieve the goals of tasks 7.1 and a private space for partners only as a discussion space and document repository.

Communication channels

Communication channels [M3;T1.2] Definition of communication channels within the consortium, the EC and other parties out of the project

Data Management Plan

Data Management Plan [M6, M18 and M36; T1.3] A report describing the data management life cycle for all data sets that will be collected, processed or generated by the research project. It is a document outlining how research data will be handled during a research project, and even after the project is completed, describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved. The first version of the DMP is delivered at M6 in compliance with the template provided by the Commission. The DMP will be updated at least by the mid-term and final review to fine-tune it to the data generated and the uses identified by the consortium.

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Publications

Music in newspapers - interdisciplinary opportunities and data-related challenges

Author(s): Cynthia C. S. Liem
Published in: Proceedings of the 5th International Conference on Digital Libraries for Musicology - DLfM '18, 2018, Page(s) 47-51
DOI: 10.1145/3273024.3273032

End-to-End Sound Source Separation Conditioned On Instrument Labels

Author(s): Slizovskaia, Olga; Kim, Leo; Haro, Gloria; Gomez, Emilia
Published in: 2019 International Conference on Acoustics, Speech, and Signal Processing., Issue 2, 2019

A Framework for Multi-f0 Modeling in SATB Choir Recordings

Author(s): Cuesta, H., Gómez E., & Chandna P.
Published in: Sound and Music Computing (SMC) Conference., 2019

Analysis of Intonation in Unison Choir Singing

Author(s): Cuesta, H., Gómez E., Martorell A., & Loáiciga F.
Published in: 15th International Conference on Music Perception and Cognition (ICMPC), 2018
DOI: 10.5281/zenodo.1319597

Mapping by Observation: Building a User-Tailored Conducting System From Spontaneous Movements

Author(s): Álvaro Sarasúa, Julián Urbano, Emilia Gómez
Published in: Frontiers in Digital Humanities, Issue 6, 2019, ISSN 2297-2668
DOI: 10.3389/fdigh.2019.00003

Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners

Author(s): Gómez, Emilia; Blaauw, Merlijn; Bonada, Jordi; Chandna, Pritish; Cuesta, Helena
Published in: 2018 Joint Workshop on Machine Learning for Music. The Federated Artificial Intelligence Meeting (FAIM), Issue 3, 2018