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Towards Richer Online Music Public-domain Archives

Deliverables

Mid-term evaluation

Mid-term evaluation [M27; T6.1] This deliverable includes the description of the pilots, in terms of user engagement, number of users involved, number and type of activities undertaken (e.g., methods used). It will also report eventual deviations with respect to the pilot planning defined in D6.2 and reasons for that.

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.

Progress/ Interim report

Progress/ Interim report [M24; T8.1] This report includes M12-24 activity and management report and describe work status/main scientific achievements, technical or managerial consortium problems, dissemination exploitation activities, indicative man months spent for that period and also to provide any policy relevant updates.

Planning for the execution of pilots in real life settings

Planning for the execution of pilots in real life settings [M14; T6.1] This report sets up the pilot phase by outlining a planning for pilot activities, user recruitment strategies, general pilot coordination and technical support, eventual acquisition of user devices to run the pilot activities (e.g., tablets, SIM cards, etc.).

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.

Score edition component

Score edition component [M12, M34; T5.2] This deliverable will consist on a digital score edition tool according to current standards (e.g. MEI schema). First release: Allowing basic access to and annotation (at the measure level) of scores and metadata Second release: Allow detailed linking and annotation across and between score documents and audio recordings

Data infrastructure

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

Final evaluation

Final evaluation [M36; T6.1] Overall results of the entire pilot phases

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.

Crowd evaluation methodologies

Crowd evaluation methodologies [M20; T4.1]. This deliverable contains the crowd-based ground truth provision and evaluation methodologies for the WP3-technology. It also contains the results of crowdsourcing experiments to elicit novel non-obvious music descriptors relevant to the different TROMPA-audiences, which feed the technology development in WP3.

Visual analysis of scanned scores

Visual analysis of scanned scores [M29; T3.4] Technologies for visual analysis and description of scanned scores

Working prototype for scholars

Working prototype for scholars [M24, M34; T6.2] Deliverable describing the music scholar prototype.

Working prototype for singers

Working prototype for singers [M24, M34; T6.5] Deliverable describing the singer prototype.

Working prototype for music enthusiasts

Working prototype for music enthusiasts [M24, M34; T6.6] Deliverable describing the music enthusiast prototype.

Working prototype for instrument players

Working prototype for instrument players [M24, M34; T6.4] Deliverable describing the instrument player prototype.

Working prototype for orchestras

Working prototype for orchestras [M24, M34; T6.3] Deliverable describing the orchestra prototype.

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

Recognizing Musical Entities in User-generated Content

Author(s): Lorenzo Porcaro, Horacio Saggion
Published in: Computación y Sistemas, Issue 23/3, 2019, ISSN 1405-5546
DOI: 10.13053/cys-23-3-3280

Music Tempo Estimation: Are We Done Yet?

Author(s): Hendrik Schreiber, Julián Urbano, Meinard Müller
Published in: Transactions of the International Society for Music Information Retrieval, Issue 3/1, 2020, Page(s) 111, ISSN 2514-3298
DOI: 10.5334/tismir.43

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

Demo: VOICEFUL: Voice Analysis, Transformation and Synthesis on the Web.

Author(s): Mayor O., Janer J., Parra H., Sarasúa, Á.
Published in: Web Audio Conference 2019, 2019

Choir Singing Synthesis for Rehearsal Tools with Large-scale Multilingual Repertoires.

Author(s): Sarasúa, Á., Janer, J., Mayor, O., Bonada J., & Blaauw. M.
Published in: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020

Microtask crowdsourcing for music score Transcriptions: an experiment with error detection.

Author(s): Samiotis, I. P., Qiu, S., Mauri, A., Liem, C. C., Lofi, C., & Bozzon, A.
Published in: 21st Conference of the International Society for Music Information Retrieval (ISMIR 2020)., 2020

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

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

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: Issue 1, 2018

Music in newspapers - interdisciplinary opportunities and data-related challenges

Author(s): Liem, C.C.S.
Published in: DLfM '18 Proceedings of the 5th International Conference on Digital Libraries for Musicology, Issue 3, 2018

The MediaEval 2018 AcousticBrainz genre task: content-based music genre recognition from multiple sources

Author(s): Dmitry Bogdanov; Porter, A.; Urbano, J.; Schreiber, H.
Published in: Proceedings of the MediaEval 2018 Workshop, 2018

(F-TEMPO): a new approach to a finding aid for musicians and librarians.

Author(s): Crawford, T.
Published in: IAML Congress 2019 (International Association of Music Libraries and Sound Archives), 2019

Measuring Diversity of Artificial Intelligence Conferences

Author(s): Freire, Ana; Porcaro, Lorenzo; Gómez, Emilia
Published in: AAAI Workshop on Diversity in Artificial Intelligence (AIDBEI 2021), Issue 12, 2021

WGANSing: A Multi-Voice Singing Voice Synthesizer Based on the Wasserstein-GAN

Author(s): Pritish Chandna, Merlijn Blaauw, Jordi Bonada, Emilia Gomez
Published in: 2019 27th European Signal Processing Conference (EUSIPCO), 2019, Page(s) 1-5
DOI: 10.23919/eusipco.2019.8903099

End-to-end Sound Source Separation Conditioned on Instrument Labels

Author(s): Olga Slizovskaia, Leo Kim, Gloria Haro, Emilia Gomez
Published in: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, Page(s) 306-310
DOI: 10.1109/icassp.2019.8683800

Semi-supervised Learning for Singing Synthesis Timbre

Author(s): Bonada, Jordi; Blaauw, Merlijn
Published in: IEEE International Conference on Acoustics, Speech and Signal Processing, 2021

A Case Study of Deep-Learned Activations via Hand-Crafted Audio Features

Author(s): Slizovskaia, Olga; Gómez, Emilia; Haro, Gloria
Published in: Issue 1, 2018

Language-Sensitive Music Emotion Recognition Models: are We Really There Yet?

Author(s): Juan Sebastian Gomez-Canon, Estefania Cano, Ana Gabriela Pandrea, Perfecto Herrera, Emilia Gomez
Published in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, Page(s) 576-580
DOI: 10.1109/icassp39728.2021.9413721

Accurate and Scalable Version Identification Using Musically-Motivated Embeddings

Author(s): Furkan Yesiler, Joan Serra, Emilia Gomez
Published in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, Page(s) 21-25
DOI: 10.1109/icassp40776.2020.9053793

A Vocoder Based Method for Singing Voice Extraction

Author(s): Pritish Chandna, Merlijn Blaauw, Jordi Bonada, Emilia Gomez
Published in: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, Page(s) 990-994
DOI: 10.1109/icassp.2019.8683323

Towards Richer Online Music Public-domain Archives: Providing enriched access to classical music encodings.

Author(s): Weigl, D. M., Liem, C., Gómez, E., Crawford, T., Ahmed, R., Klerkx, W., & Goebl, W
Published in: Music Encoding Conference 2019, 2019

A New Perspective on Score Standardization

Author(s): Julián Urbano, Harlley Lima, Alan Hanjalic
Published in: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019, Page(s) 1061-1064
DOI: 10.1145/3331184.3331315

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

Read/Write Digital Libraries for Musicology

Author(s): David M. Weigl, Werner Goebl, Alex Hofmann, Tim Crawford, Federico Zubani, Cynthia C. S. Liem, Alastair Porter
Published in: 7th International Conference on Digital Libraries for Musicology, 2020, Page(s) 48-52
DOI: 10.1145/3424911.3425519

Sequence-to-Sequence Singing Synthesis Using the Feed-Forward Transformer

Author(s): Merlijn Blaauw, Jordi Bonada
Published in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, Page(s) 7229-7233
DOI: 10.1109/icassp40776.2020.9053944

Hundreds of Thousands of Pieces in MEI: Encoding Tablatures at Scale

Author(s): Ahmed, R.; Crawford, T.; Lewis, D.
Published in: Music Encoding Conference., 2019

Music recommendation diversity: a tentative framework and preliminary results

Author(s): Porcaro, Lorenzo; Castillo, Carlos; Gómez Gutiérrez, Emilia, 1975-
Published in: 1st Workshop on Designing Human-Centric MIR Systems, Issue 1, 2019

Interweaving and Enriching Digital Music Collections for Scholarship, Performance, and Enjoyment

Author(s): David M. Weigl, Werner Goebl, Tim Crawford, Aggelos Gkiokas, Nicolas F. Gutierrez, Alastair Porter, Patricia Santos, Casper Karreman, Ingmar Vroomen, Cynthia C. S. Liem, Álvaro Sarasúa, Marcel van Tilburg
Published in: 6th International Conference on Digital Libraries for Musicology, 2019, Page(s) 84-88
DOI: 10.1145/3358664.3358666

Exploring Artist Gender Bias in Music Recommendation

Author(s): Shakespeare, Dougal; Porcaro, Lorenzo; Gómez Gutiérrez, Emilia, 1975-; Castillo, Carlos
Published in: 2nd Workshop on the Impact of Recommender Systems (ImpactRS), at the 14th ACM Conference on Recommender Systems, Issue 20, 2020

Content Based Singing Voice Extraction from a Musical Mixture

Author(s): Pritish Chandna, Merlijn Blaauw, Jordi Bonada, Emilia Gomez
Published in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, Page(s) 781-785
DOI: 10.1109/icassp40776.2020.9053024

A Model for evaluating popularity and semantic information variations in radio listening sessions

Author(s): Porcaro, Lorenzo; Gómez Gutiérrez, Emilia, 1975-
Published in: 13th ACM Conference on Recommender Systems (RecSys 2019), 2019