Biblio

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Buldú, J. M., Cano P., Koppenberger M., Almendral J., & Boccaletti S. (2007).  The complex network of musical tastes. New Journal of Physics. 9, Abstract
Zanin, M., Cano P., Buldú J. M., & Celma Ò. (2008).  Complex networks in recommendation systems. Proceedings of the 2nd WSEAS International Conference on Computer Engineering and Applications. Abstract
Şentürk, S., & Serra X. (2016).  Composition Identification in Ottoman-Turkish Makam Music Using Transposition-Invariant Partial Audio-Score Alignment. 13th Sound and Music Computing Conference (SMC 2016). 434-441. Abstract
Barroso, E., & Pérez A. (2007).  Composition through Spectral Modeling Synthesis and Pure Data. Abstract
Herrera, P., & Loureiro R. (1996).  Comprensión de escenarios sonoros.
Şentürk, S. (2016).  Computational Analysis of Audio Recordings and Music Scores for the Description and Discovery of Ottoman-Turkish Makam Music. Department of Information and Communication Technologies. 357. Abstract
Özaslan, T. (2013).  Computational Analysis of Expressivity in Classical Guitar Performances. Department of Information and Communication Technologies. 97. Abstract
Bozkurt, B. (2015).  Computational Analysis of Overall Melodic Progression for Turkish Makam Music. (Ayari, Mondher, Ed.).Penser l'improvisation. 289-298. Abstract
Papiotis, P., Marchini M., & Maestre E. (2012).  Computational analysis of solo versus ensemble performance in string quartets: Dynamics and Intonation. 12th International Conference on Music Perception and Cognition. Abstract
application/pdf iconICMPC2012-Papiotis.pdf
Laurier, C., & Herrera P. (2007).  A computational approach to classify music by emotion. European Computing Conference. Abstract
Gouyon, F. (2005).  A computational approach to rhythm description --- Audio features for the computation of rhythm periodicity functions and their use in tempo induction and music content processing. Department of Information and Communication Technologies. Abstract
Papiotis, P. (2016).  A computational approach to studying interdependence in string quartet performance. Abstract
Gulati, S. (2016).  Computational Approaches for Melodic Description in Indian Art Music Corpora. Department of Information and Communication Technologies. 305. Abstract
Koduri, G. K., Miron M., Serrà J., & Serra X. (2011).  Computational approaches for the understanding of melody in Carnatic music. International Society for Music Information Retrieval Conference (ISMIR). 157-162. Abstract
Serra, X. (2014).  Computational Approaches to the Art Music Traditions of India and Turkey. Journal of New Music Research. 43(1), 1-2.
application/pdf iconSerra-X-JNMR-2014.pdf
Kroher, N., Gómez E., Sordo M., Gómez-Martín F., Díaz-Báñez J. M., Mora J., et al. (2014).  Computational ethnomusicology: a study of flamenco and Arab-Andalusian vocal music. 4th International Workshop On Folk Music Analysis. Abstract
application/pdf iconFMA2014_submission_kroher_et_al.pdf
Gómez, E., Herrera P., & Gómez-Martín F. (2013).  Computational Ethnomusicology: perspectives and challenges. Journal of New Music Research. 42(2), 111-112.
Alvarez, F. Y. (2019).  A Computational Model for Spectral Modulation and Speech Perception Performance of Cochlear Implant Users. Abstract
Hazan, A. (2006).  Computational Modeling of Expressive Music Performance New Machine Learning Approaches for Dealing With Real-World Data. Abstract
Hazan, A., Herrera P., Marxer R., Grachten M., & Purwins H. (2007).  Computational Modeling of Statistical Learning of Tone Sequences (Poster). International Conference on Cognitive and Neural Systems (ICCNS 2007). Abstract
Siquier Peñafort, M. (2017).  Computational modelling of expressive music performance in hexaphonic guitar. Abstract
Giraldo, S. (2016).  Computational Modelling of Expressive Music Performance in Jazz Guitar: A Machine Learning Approach. Department of Information and Communication Technologies. 158.
Giraldo, S., & Ramirez R. (2015).  Computational Modelling of Ornamentation in Jazz Guitar Music. International Symposium in Performance Science. 150-151.
application/pdf iconISPS 2015
Kroher, N., Gómez E., Guastavino C., Gómez-Martín F., & Bonada J. (2014).  Computational models for perceived melodic similarity in a cappella flamenco cantes. 15th International Society for Music Information Retrieval Conference.
application/pdf iconMelodicSimilarityCameraReady.pdf
Purwins, P., Herrera P., Grachten M., Hazan A., Marxer R., & Serra X. (2008).  Computational Models of Music Perception and Cognition I: The Perceptual and Cognitive Processing Chain. Physics of Life Reviews. 5(3), 151-168. Abstract
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