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Gómez, E. (2006).  Tonal description of polyphonic audio for music content processing. INFORMS Journal on Computing, Special Cluster on Computation in Music. 18, Abstract
Gómez, P., Pikrakis A., Mora J., Díaz-Báñez J. M., Gómez E., Escobar Borrego F., et al. (2012).  Automatic Detection of Melodic Patterns in Flamenco Singing by Analyzing Polyphonic Music Recordings. III Interdisciplinary Conference on Flamenco Research (INFLA) and II International Workshop of Folk Music Analysis (FMA). Abstract
Gómez, E. (2011).  Integrating Different Knowledge Sources for the Computational Modeling of Flamenco Music. (Müller, M., Goto, M., Dixon, S., Ed.).Multimodal Music Processing (Dagstuhl Seminar 11041) - Dagstuhl Reports. 1(1), 82-83. Abstract
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.