Biblio

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2019
Porcaro, L., & Gómez E. (2019).  A Model for Evaluating Popularity and Semantic Information Variations in Radio Listening Sessions. 1st Workshop on the Impact of Recommender Systems (ImpactRS), at the 13th ACM Conference on Recommender Systems (RecSys 2019). Abstract
Slizovskaia, O., Kim L., Haro G., & Gómez E. (2019).  End-to-End Sound Source Separation Conditioned On Instrument Labels. 2019 International Conference on Acoustics, Speech, and Signal Processing. Abstract
Chandna, P., Blaauw M., Bonada J., & Gomez E. (2019).  A Vocoder Based Method For Singing Voice Extraction. 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019). Abstract
Porcaro, L., & Gómez E. (2019).  20 Years of Playlists: A Statistical Analysis on Popularity and Diversity. 20th Conference of the International Society for Music Information Retrieval (ISMIR 2019). Abstract
2018
Fernández-Macías, E., Gomez E., Hernández-Orallo J., Loe B. - S., Martens B., Martínez-Plumed F., et al. (2018).  A multidisciplinary task-based perspective for evaluating the impact of AI autonomy and generality on the future of work. Workshop on architectures and evaluation for generality, autonomy and progress in AI, IJCAI-ECAI 2018, AAMAS 2018 AND ICML 2018.
Gomez, E., Blaauw M., Bonada J., Chandna P., & Cuesta H. (2018).  Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners. Keynote speech, 2018 Joint Workshop on Machine Learning for Music. The Federated Artificial Intelligence Meeting (FAIM), a joint workshop program of ICML, IJCAI/ECAI, and AAMAS.
Cuesta, H., Gómez E., Martorell A., & Loáiciga F. (2018).  Analysis of Intonation in Unison Choir Singing. 15th International Conference on Music Perception and Cognition (ICMPC).
2017
Chandna, P., Miron M., Janer J., & Gómez E. (2017).  Monoaural Audio Source Separation Using Deep Convolutional Neural Networks. 13th International Conference on Latent Variable Analysis and Signal Separation (LVA ICA2017).
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