Risultati finali Documents, reports (16) 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 Demonstrators, pilots, prototypes (5) 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. Websites, patent fillings, videos etc. (2) 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 Open Research Data Pilot (1) 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. Pubblicazioni Conference proceedings (39) Transfer learning from speech to music: towards language-sensitive emotion recognition models Autori: Gómez-Cañón, Juan Sebastián; Cano, Estefanía; Herrera, Perfecto; Gómez, Emilia Pubblicato in: Proceedings of the 28th European Signal Processing Conference (EUSIPCO), 2021 Editore: IEEE DOI: 10.5281/zenodo.4076790 Less is more: Faster and better music version identification with embedding distillation Autori: Yesiler, Furkan; Serra, Joan; Gomez, Emilia Pubblicato in: Proceedings of the 21stInternational Society for Music Information Retrieval Conference, 2020 Editore: International Society for Music Information Retrieval Conference DOI: 10.5281/zenodo.4245569 Vocoder-Based Speech Synthesis from Silent Videos Autori: Daniel Michelsanti, Olga Slizovskaia, Gloria Haro, Emilia Gómez, Zheng-Hua Tan, Jesper Jensen Pubblicato in: Interspeech 2020, 2020, Page(s) 3530-3534 Editore: ISCA DOI: 10.21437/interspeech.2020-1026 20 Years of Playlists: A Statistical Analysis on Popularity and Diversity Autori: Porcaro, Lorenzo; Gómez Gutiérrez, Emilia, 1975- Pubblicato in: 20th International Society for Music Information Retrieval Conference, Issue 1, 2019 Editore: International Society for Music Information Retrieval Conference DOI: 10.5281/zenodo.3527757 A deep learning based analysis-synthesis framework for unison singing Autori: Chandna, Pritish; Cuesta, Helena; Gómez, Emilia Pubblicato in: Proceedings of the 21st International Society for Music Information Retrieval Conference, 2020, Page(s) 598-604 Editore: International Society for Music Information Retrieval DOI: 10.5281/zenodo.4245501 Rehearsal Encodings with a Social Life. Autori: Weigl, D. M. and Goebl, W. Pubblicato in: Music Encoding Conference (MEC2020), 2020 Editore: De Luca, E.; and Flanders, J., editors. DOI: 10.17613/5ae5-8387 Da-TACOS: A Dataset for Cover Song Identification and Understanding Autori: Yesiler, Furkan; Tralie, Chris; Correya, Albin; Silva, Diego Furtado; Tovstogan, Philip; Gomez, Emilia; Serra, Xavier Pubblicato in: Proceedings of the 20th International Society for Music Information Retrieval Conference, ISMIR, Issue 1, 2019 Editore: International Society for Music Information Retrieval Conference DOI: 10.5281/zenodo.3527810 Combining musical features for cover detection Autori: Doras, Guillaume; Yesiler, Furkan; Serra, Joan; Gomez, Emilia; Peeters, Geoffroy Pubblicato in: Proceedings of the 21st International Society for Music Information Retrieval Conference, 2020, Page(s) 279-286 Editore: International Society for Music Information Retrieval DOI: 10.5281/zenodo.4245423 Music in newspapers - interdisciplinary opportunities and data-related challenges Autori: Liem, C.C.S. Pubblicato in: DLfM '18 Proceedings of the 5th International Conference on Digital Libraries for Musicology, Issue 3, 2018 Editore: ACM The MediaEval 2018 AcousticBrainz genre task: content-based music genre recognition from multiple sources Autori: Dmitry Bogdanov; Porter, A.; Urbano, J.; Schreiber, H. Pubblicato in: Proceedings of the MediaEval 2018 Workshop, 2018 Editore: MediaEval (F-TEMPO): a new approach to a finding aid for musicians and librarians. Autori: Crawford, T. Pubblicato in: IAML Congress 2019 (International Association of Music Libraries and Sound Archives), 2019 Editore: IAML Measuring Diversity of Artificial Intelligence Conferences Autori: Freire, Ana; Porcaro, Lorenzo; Gómez, Emilia Pubblicato in: AAAI Workshop on Diversity in Artificial Intelligence (AIDBEI 2021), Issue 12, 2021 Editore: AIDBEI Multiple F0 Estimation in Vocal Ensembles using Convolutional Neural Networks Autori: Cuesta, Helena; McFee, Brian; Gomez, Emilia Pubblicato in: 21st International Society for Music Information Retrieval, 2020 Editore: International Society for Music Information Retrieval DOI: 10.5281/zenodo.4245433 WGANSing: A Multi-Voice Singing Voice Synthesizer Based on the Wasserstein-GAN Autori: Pritish Chandna, Merlijn Blaauw, Jordi Bonada, Emilia Gomez Pubblicato in: 2019 27th European Signal Processing Conference (EUSIPCO), 2019, Page(s) 1-5, ISBN 978-9-0827-9703-9 Editore: IEEE DOI: 10.23919/eusipco.2019.8903099 The AcousticBrainz Genre Dataset: Multi-Source, Multi-Level, Multi-Label, and Large-Scale Autori: Dmitry Bogdanov; Alastair Porter; Hendrik Schreiber; Julián Urbano; Sergio Oramas Pubblicato in: International Society for Music Information Retrieval Conference 2019, Issue 28, 2019 Editore: Ubiquity Press DOI: 10.5281/zenodo.3527817 End-to-end Sound Source Separation Conditioned on Instrument Labels Autori: Olga Slizovskaia, Leo Kim, Gloria Haro, Emilia Gomez Pubblicato in: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, Page(s) 306-310, ISBN 978-1-4799-8131-1 Editore: IEEE DOI: 10.1109/icassp.2019.8683800 Semi-supervised Learning for Singing Synthesis Timbre Autori: Bonada, Jordi; Blaauw, Merlijn Pubblicato in: IEEE International Conference on Acoustics, Speech and Signal Processing, 2021 Editore: IEEE Joyful for you and tender for us: the influence of individual characteristics and language on emotion labeling and classification Autori: Gómez-Cañón, Juan Sebastián; Cano, Estefanía; Herrera, Perfecto; Gómez, Emilia Pubblicato in: Proceedings of the 21st International Society of Music Information Retrieval Conference, 2020 Editore: International Society of Music Information Retrieval Conference (ISMIR), DOI: 10.5281/zenodo.4245568 A Case Study of Deep-Learned Activations via Hand-Crafted Audio Features Autori: Slizovskaia, Olga; Gómez, Emilia; Haro, Gloria Pubblicato in: Issue 1, 2018 Editore: Joint Workshop on Machine Learning for Music Language-Sensitive Music Emotion Recognition Models: are We Really There Yet? Autori: Juan Sebastian Gomez-Canon, Estefania Cano, Ana Gabriela Pandrea, Perfecto Herrera, Emilia Gomez Pubblicato in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, Page(s) 576-580, ISBN 978-1-7281-7605-5 Editore: IEEE DOI: 10.1109/icassp39728.2021.9413721 Accurate and Scalable Version Identification Using Musically-Motivated Embeddings Autori: Furkan Yesiler, Joan Serra, Emilia Gomez Pubblicato in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, Page(s) 21-25, ISBN 978-1-5090-6631-5 Editore: IEEE DOI: 10.1109/icassp40776.2020.9053793 Statistical Significance Testing in Information Retrieval: An Empirical Analysis of Type I, Type II and Type III Errors Autori: Urbano Merino, J.; De Lima, H.A.; Hanjalic, A. Pubblicato in: SIGIR'19 Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Issue 20, 2019 Editore: ACM DOI: 10.1145/3331184.3331259 A Vocoder Based Method for Singing Voice Extraction Autori: Pritish Chandna, Merlijn Blaauw, Jordi Bonada, Emilia Gomez Pubblicato in: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, Page(s) 990-994, ISBN 978-1-4799-8131-1 Editore: IEEE DOI: 10.1109/icassp.2019.8683323 Towards Richer Online Music Public-domain Archives: Providing enriched access to classical music encodings. Autori: Weigl, D. M., Liem, C., Gómez, E., Crawford, T., Ahmed, R., Klerkx, W., & Goebl, W Pubblicato in: Music Encoding Conference 2019, 2019 Editore: De Luca, E.; and Flanders, J., editors A New Perspective on Score Standardization Autori: Julián Urbano, Harlley Lima, Alan Hanjalic Pubblicato in: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019, Page(s) 1061-1064, ISBN 9781450361729 Editore: ACM DOI: 10.1145/3331184.3331315 Music in newspapers - interdisciplinary opportunities and data-related challenges Autori: Cynthia C. S. Liem Pubblicato in: Proceedings of the 5th International Conference on Digital Libraries for Musicology - DLfM '18, 2018, Page(s) 47-51, ISBN 9781-450365222 Editore: ACM Press DOI: 10.1145/3273024.3273032 End-to-End Sound Source Separation Conditioned On Instrument Labels Autori: Slizovskaia, Olga; Kim, Leo; Haro, Gloria; Gomez, Emilia Pubblicato in: 2019 International Conference on Acoustics, Speech, and Signal Processing., Issue 2, 2019 Editore: IEEE A Framework for Multi-f0 Modeling in SATB Choir Recordings Autori: Cuesta, H., Gómez E., & Chandna P. Pubblicato in: Sound and Music Computing (SMC) Conference., 2019 Editore: SMC Analysis of Intonation in Unison Choir Singing Autori: Cuesta, H., Gómez E., Martorell A., & Loáiciga F. Pubblicato in: 15th International Conference on Music Perception and Cognition (ICMPC), 2018 Editore: Universitty of Graz DOI: 10.5281/zenodo.1319597 Read/Write Digital Libraries for Musicology Autori: David M. Weigl, Werner Goebl, Alex Hofmann, Tim Crawford, Federico Zubani, Cynthia C. S. Liem, Alastair Porter Pubblicato in: 7th International Conference on Digital Libraries for Musicology, 2020, Page(s) 48-52, ISBN 9781450387606 Editore: ACM DOI: 10.1145/3424911.3425519 Sequence-to-Sequence Singing Synthesis Using the Feed-Forward Transformer Autori: Merlijn Blaauw, Jordi Bonada Pubblicato in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, Page(s) 7229-7233, ISBN 978-1-5090-6631-5 Editore: IEEE DOI: 10.1109/icassp40776.2020.9053944 Deep learning based source separation applied to choir ensembles Autori: Petermann, Darius; Pritish Chandna; Cuesta, Helena; Bonada, Jordi; Gomez, Emilia Pubblicato in: Proceedings of the 21st International Society for Music Information Retrieval Conference, 2020, Page(s) 733-739 Editore: International Society for Music Information Retrieval DOI: 10.5281/zenodo.4245535 Hundreds of Thousands of Pieces in MEI: Encoding Tablatures at Scale Autori: Ahmed, R.; Crawford, T.; Lewis, D. Pubblicato in: Music Encoding Conference., 2019 Editore: De Luca, E.; and Flanders, J., editors Music recommendation diversity: a tentative framework and preliminary results Autori: Porcaro, Lorenzo; Castillo, Carlos; Gómez Gutiérrez, Emilia, 1975- Pubblicato in: 1st Workshop on Designing Human-Centric MIR Systems, Issue 1, 2019 Editore: International Society for Music Information Retrieval Interweaving and Enriching Digital Music Collections for Scholarship, Performance, and Enjoyment Autori: 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 Pubblicato in: 6th International Conference on Digital Libraries for Musicology, 2019, Page(s) 84-88, ISBN 9781450372398 Editore: ACM DOI: 10.1145/3358664.3358666 Solos: A Dataset for Audio-Visual Music Analysis Autori: Montesinos, Juan F.; Slizovskaia, Olga; Haro, Gloria Pubblicato in: 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), Issue 23, 2020 Editore: IEEE Exploring Artist Gender Bias in Music Recommendation Autori: Shakespeare, Dougal; Porcaro, Lorenzo; Gómez Gutiérrez, Emilia, 1975-; Castillo, Carlos Pubblicato in: 2nd Workshop on the Impact of Recommender Systems (ImpactRS), at the 14th ACM Conference on Recommender Systems, Issue 20, 2020 Editore: ACM Content Based Singing Voice Extraction from a Musical Mixture Autori: Pritish Chandna, Merlijn Blaauw, Jordi Bonada, Emilia Gomez Pubblicato in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, Page(s) 781-785, ISBN 978-1-5090-6631-5 Editore: IEEE DOI: 10.1109/icassp40776.2020.9053024 A Model for evaluating popularity and semantic information variations in radio listening sessions Autori: Porcaro, Lorenzo; Gómez Gutiérrez, Emilia, 1975- Pubblicato in: 13th ACM Conference on Recommender Systems (RecSys 2019), 2019 Editore: ACM Peer reviewed articles (4) Recognizing Musical Entities in User-generated Content Autori: Lorenzo Porcaro, Horacio Saggion Pubblicato in: Computación y Sistemas, Issue 23/3, 2019, ISSN 1405-5546 Editore: Centro de Investigacion en Computacion (CIC) del Instituto Politecnico Nacional (IPN) DOI: 10.13053/cys-23-3-3280 Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing Autori: Sebastian Rosenzweig, Helena Cuesta, Christof Weiß, Frank Scherbaum, Emilia Gómez, Meinard Müller Pubblicato in: Transactions of the International Society for Music Information Retrieval, Issue 3/1, 2020, Page(s) 98-110, ISSN 2514-3298 Editore: Ubiquity Press DOI: 10.5334/tismir.48 Music Tempo Estimation: Are We Done Yet? Autori: Hendrik Schreiber, Julián Urbano, Meinard Müller Pubblicato in: Transactions of the International Society for Music Information Retrieval, Issue 3/1, 2020, Page(s) 111, ISSN 2514-3298 Editore: Ubiquity press DOI: 10.5334/tismir.43 Mapping by Observation: Building a User-Tailored Conducting System From Spontaneous Movements Autori: Álvaro Sarasúa, Julián Urbano, Emilia Gómez Pubblicato in: Frontiers in Digital Humanities, Issue 6, 2019, ISSN 2297-2668 Editore: Frontiers DOI: 10.3389/fdigh.2019.00003 Other (6) Demo: VOICEFUL: Voice Analysis, Transformation and Synthesis on the Web. Autori: Mayor O., Janer J., Parra H., Sarasúa, Á. Pubblicato in: Web Audio Conference 2019, 2019 Editore: Web Audio Conference Choir Singing Synthesis for Rehearsal Tools with Large-scale Multilingual Repertoires. Autori: Sarasúa, Á., Janer, J., Mayor, O., Bonada J., & Blaauw. M. Pubblicato in: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020 Editore: IEEE Microtask crowdsourcing for music score Transcriptions: an experiment with error detection. Autori: Samiotis, I. P., Qiu, S., Mauri, A., Liem, C. C., Lofi, C., & Bozzon, A. Pubblicato in: 21st Conference of the International Society for Music Information Retrieval (ISMIR 2020)., 2020 Editore: International Society for Music Information Retrieval Analysis of Intonation in Unison Choir Singing Autori: Cuesta; H.; Gómez E.; Martorell A.; Loáiciga F. Pubblicato in: 15th International Conference on Music Perception and Cognition (ICMPC), 2018 Editore: International Conference on Music Perception and Cognition Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners Autori: Gómez, Emilia; Blaauw, Merlijn; Bonada, Jordi; Chandna, Pritish; Cuesta, Helena Pubblicato in: 2018 Joint Workshop on Machine Learning for Music. The Federated Artificial Intelligence Meeting (FAIM), Issue 3, 2018 Editore: CML, IJCAI/ECAI, and AAMAS Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners Autori: Gómez, Emilia; Blaauw, Merlijn; Bonada, Jordi; Chandna, Pritish; Cuesta, Helena Pubblicato in: Issue 1, 2018 Editore: Joint Workshop on Machine Learning for Music Book chapters (1) Playing with a Web of Music: Connecting and enriching online music repositories Autori: Weigl, D. M. and Goebl, W. Pubblicato in: Music – Media – History: Re-Thinking Musicology in an Age of Digital Media, 2021, ISBN 9783837651454 Editore: In Matej Santi and Elias Berner (Edsit.) È in corso la ricerca di dati su OpenAIRE... Si è verificato un errore durante la ricerca dei dati su OpenAIRE Nessun risultato disponibile
