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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.
Gong, R. (2018).  Automatic Assessment of Singing Voice Pronunciation: A Case Study with Jingju Music. Department of Information and Communications Technologies. xxxii + 235. Abstract
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).
Pons, J., Nieto O., Prockup M., Schmidt E. M., Ehmann A. F., & Serra X. (2018).  End-to-end learning for music audio tagging at scale. 19th International Society for Music Information Retrieval Conference (ISMIR2018). Abstract