Biblio

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Conference Paper
Slizovskaia, O., Gómez E., & Haro G. G. (2017).  Correspondence between audio and visual deep models for musical instrument detection in video recordings. 18th International Society for Music Information Retrieval Conference (ISMIR2017, LBD). Abstract
Yesiler, F., Tralie C., Correya A., Silva D. F., Tovstogan P., Gómez E., et al. (2019).  Da-TACOS: A dataset for cover song identification and understanding. International Society for Music Information Retrieval (ISMIR). 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.
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
Bogdanov, D., Wack N., Gómez E., Gulati S., Herrera P., Mayor O., et al. (2013).  ESSENTIA: an Audio Analysis Library for Music Information Retrieval. International Society for Music Information Retrieval Conference (ISMIR'13). 493-498. Abstract
Bogdanov, D., Wack N., Gómez E., Gulati S., Herrera P., Mayor O., et al. (2013).  ESSENTIA: an Open-Source Library for Sound and Music Analysis. ACM International Conference on Multimedia (MM'13). 855-858. Abstract
application/pdf iconessentia_acmmm13.pdf
Gómez, E., & Herrera P. (2004).  Estimating The Tonality Of Polyphonic Audio Files Cognitive Versus Machine Learning Modelling Strategies. 5th International Society for Music Information Retrieval (ISMIR) Conference. 92-95. Abstract
application/pdf iconGómezHerrera-ISMIR-2004-page-92.pdf
Gómez, E., & Herrera P. (2006).  Evaluation and applications of tonal profiles for automatic music tonality description. Abstract
Oramas, S., Gómez F., Gómez E., & Mora J. (2015).  FlaBase: Towards the Creation of a Flamenco Music Knowledge Base. 16th International Society for Music Information Retrieval Conference. Abstract
application/pdf iconflabase.pdf
Cuesta, H., Gómez E., & Chandna P. (2019).  A Framework for Multi-f0 Modeling in SATB Choir Recordings. Sound and Music Computing Conference. 447-453. Abstract
Molina, E., Barbancho I., Gómez E., Barbancho A. M., & Tardón L. J. (2013).  Fundamental frequency alignment vs note-based melodic similarity for singing voice assessment. 8th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
application/pdf iconSingingAssessment_ICASSP2013.pdf
Miron, M., Janer J., & Gómez E. (2017).  Generating data to train convolutional neural networks for classical music source separation. Proceedings of the 14th Sound and Music Computing Conference. 227-233.
Janer, J., Gómez E., Martorell A., Miron M., & de Wit B. (2016).  Immersive Orchestras: audio processing for orchestral music VR content. VSGAMES 2016 - 8th International Conference on Virtual Worlds and Games for Serious Applications. Abstract
Kroher, N., & Gómez E. (2014).  Improving accompanied Flamenco singing voice transcription by combining vocal detection and predominant melody extraction.. International Computer Music Conference/Sound and Music Computing Conference. Abstract
application/pdf iconCameraReady_VoicingDetection.pdf
Zapata, J. R., & Gómez E. (2012).  Improving Beat Tracking in the presence of highly predominant vocals using source separation techniques: Preliminary study. The 9th International Symposium on Computer Music Modeling and Retrieval (CMMR) . 583-590.
application/pdf iconBeatracking_with_source_separation_Jose_Zapata.pdf
Cano, P., Koppenberger M., Wack N., G. Mahedero J., Masip J., Celma Ò., et al. (2005).  An Industrial-Strength Content-based Music Recommendation System. 28th Annual International ACM SIGIR Conference. Abstract
Faraldo, Á., Gómez E., Jordà S., & Herrera P. (2016).  Key Estimation in Electronic Dance Music. 38th European Conference on Information Retrieval. 335-347. Abstract
Molina-Solana, M., Arcos J. L., & Gómez E. (2008).  Learning Violinist's Expressive Trends . International Workshop on Machine Learning and Music, Held in conjunction with ICML/COLT/UAI 2008. Abstract
Gramunt, N., Desiré, Morera A., Gómez E., Herrera P., Nebot E., et al. (2019).  Lifesoundtrack: an intergenerational musical experience to promote wellbeing in people with dementia while increasing community awareness. 14th​ International Conference on Alzheimer's and Parkinson's Diseases. Abstract
Ramirez, R., Hazan A., Gómez E., & Maestre E. (2004).  A machine learning approach to expressive performance in jazz standards. ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Abstract
Mora, J., Gómez F., Gómez E., Escobar Borrego F., & Díaz-Báñez J. M. (2010).  Melodic Characterization and Similarity in A Cappella Flamenco Cantes. International Society for Music Information Retrieval Conference (ISMIR) . Abstract
application/pdf iconMelodyFlamenco-ISMIR2010.pdf
Gómez, E., Grachten M., Amatriain X., & Arcos J. L. (2003).  Melodic characterization of monophonic recordings for expressive tempo transformations. Abstract
Bosch, J., & Gómez E. (2016).  Melody extraction based on a source-filter model using pitch contour selection. 13th Sound and Music Computing Conference (SMC 2016). 67-74. Abstract
application/pdf iconSMC-postprint-bosch.pdf
Bosch, J., & Gómez E. (2015).  Melody extraction by means of a source-filter model and pitch contour characterization (MIREX 2015). Music Information Retrieval Evaluation eXchange (MIREX).
application/pdf iconJ. Bosch MIREX 2015 melody extraction submission
Bosch, J., & Gómez E. (2014).  Melody extraction in symphonic classical music: a comparative study of mutual agreement between humans and algorithms. 9th Conference on Interdisciplinary Musicology – CIM14.
application/pdf iconCIM14-Bosch.pdf
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