Biblio

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Macias, B. (1999).  Visualización 3D de la modelización sinusoidal más residual del sonido. Abstract
Macias, B. (1998).  SMS3d: An application for the visualization of SMS data. International Conference on Digital Audio Effects. Abstract
Maestre, E., Blaauw M., Bonada J., Guaus E., & Pérez A. (2010).  Statistical Modeling of Bowing Control applied to Violin Sound Synthesis. IEEE Transactions on Audio, Speech, and Language Processing .
Maestre, E. (2009).  Statistical Modeling of Violin Bowing Parameter Contours. International Computer Music Conference. Abstract
Maestre, E., Hazan A., Ramirez R., & Pérez A. (2006).  Using concatenative synthesis for expressive performance in jazz saxophone. International Computer Music Conference. Abstract
Maestre, E., Pérez A., & Ramirez R. (2010).  Gesture sampling for instrumental sound synthesis: violin bowing as a case study. International Computer Music Conference. Abstract
application/pdf iconicmc_maestre_perez_ramirez2010.pdf
Maestre, E., Scavone G., & Smith J. (2013).  Digital Modeling of Bridge Driving-Point Admittances from Measurements on Violin-Family Instruments. Stockholm Music Acoustics Conference 2013 & Sound and Music Computing Conference 2013. Abstract
application/pdf iconsmac_adm_2013_v3.pdf
Maestre, E. (2009).  Modeling instrumental gestures: an analysis/synthesis framework for violin bowing. Department of Information and Communication Technologies. Abstract
Maestre, E., & Ramirez R. (2010).  An approach to predicting bowing control parameter contours in violin performance. Intelligent Data Analysis. 14(5), 587-599.
Maestre, E., Papiotis P., Marchini M., Llimona Q., Mayor O., Pérez A., et al. (2017).  Enriched Multimodal Representations of Music Performances: Online Access and Visualization. IEEE MultiMedia. 24(1), 24-34. Abstract
Maestre, E., Bonada J., & Mayor O. (2006).  Modeling musical articulation gestures in singing voice performances. AES 121th Convention. Abstract
Maestre, E., Spa C., & Smith J. (2014).  A BOWED STRING PHYSICAL MODEL INCLUDING FINITE-WIDTH THERMAL FRICTION AND HAIR DYNAMICS. ICMC-SMC. Abstract
application/pdf iconManuscript
Maestre, E., & Gómez E. (2005).  Automatic characterization of dynamics and articulation of expressive monophonic recordings. AES 118th Convention. Abstract
Maestre, E. (2006).  Coding Instrumental Gestures. Towards a quantitative description of instrumental gestures in excitation-continuous musical instruments. Abstract
Maestre, E., Bonada J., Blaauw M., Pérez A., & Guaus E. (2007).  Acquisition of violin instrumental gestures using a commercial EMF device. International Computer Music Conference. Abstract
Maestre, E., Ramirez R., Kersten S., & Serra X. (2009).  Expressive Concatenative Synthesis by Reusing Samples from Real Performance Recordings. Computer Music Journal. 33(4), 23-42. Abstract
Marchini, M., & Purwins H. (2010).  Unsupervised Generation of Percussion Sound Sequences from a Sound Example. Sound and Music Computing Conference. Abstract
application/pdf iconMarchiniPurwinsContinuationSMC2010Final.pdf
Marchini, M., Papiotis P., & Maestre E. (2013).  Investigating the relationship between expressivity and synchronization in ensemble performance: an exploratory study. International Symposium on Performance Science, Vienna.
Marchini, M., & Purwins H. (2010).  An Unsupervised System for the Synthesis of Variations from Audio Percussion Patterns. 7th International Symposium on Computer Music Modeling and Retrieval (CMMR). 277-278. Abstract
application/pdf iconMarchiniPurwinsCMMR2010Demo.pdf
Marchini, M., & Purwins H. (2011).  Unsupervised Analysis and Generation of Audio Percussion Sequences. (Ystad, Sølvi, Aramaki, Mitsuko, Kronland-Martinet, Richard, Jensen, Kristoffer, Ed.).Exploring Music Contents. 6684, 205-218.
Marchini, M. (2010).  Unsupervised Generation of Percussion Sequences from a Sound Example. Abstract
Marchini, M. (2014).  Analysis of Ensemble Expressive Performance in String Quartets: a Statistical and Machine Learning Approach. Department of Information and Communication Technologies. Abstract
Marchini, M., Papiotis P., Maestre E., & Pérez A. (2011).  A hair ribbon deflection model for low-intrusiveness measurement of bow force in violin performance.. New Interfaces for Musical Creation (NIME 2011). Abstract
Marchini, M., Ramirez R., Papiotis P., & Maestre E. (2014).  The Sense of Ensemble: a Machine Learning Approach to Expressive Performance Modelling in String Quartets. Journal of New Music Research. 43, 303-317.
Marchini, M., Ramirez R., Papiotis P., & Maestre E. (2013).  Inducing rules of ensemble music performance: a machine learning approach. 3rd international conference on Music & Emotion, Jyväskylä.
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