Biblio
Filters: Author is E. Maestre [Clear All Filters]
A Machine Learning Approach to Expressive Performance in Jazz Standards.
( , Ed.).Multimedia Data Mining and Knowledge Discovery. Abstract
(2006).
Modeling Expressive Music Performance in Bassoon Audio Recordings.
Intelligent Computing in Signal Processing and Pattern Recognition. 345, 951-957.
(2006).
(2011).
Acquisition of violin instrumental gestures using a commercial EMF device.
International Computer Music Conference. Abstract
(2007).
Adding Dynamic Smoothing to Mixture Mosaicing Synthesis.
Spars11: Workshop on Signal Processing with Adaptive Sparse Structured Representations. Abstract
(2011).
Augmenting Sound Mosaicing with Descriptor-driven Transformation.
Digital Audio Effects. Abstract
(2010).
Aural-based detection and assessment of real versus artificially synchronized string quartet performance.
3rd International Conference on Music & Emotion. Abstract
(2013).
(2005).
(2014).
Calibration method to measure accurate bow force for real violin performances .
( , Ed.).International Computer Music Conference. 251-254. Abstract
(2009).
Combining Performance Actions with Spectral Models for Violin Sound Transformation.
International Congress on Acoustics. Abstract
(2007).
Computational analysis of solo versus ensemble performance in string quartets: Dynamics and Intonation.
12th International Conference on Music Perception and Cognition. Abstract
(2012).
Concatenative Synthesis of Expressive Saxophone Performance.
Sound and Music Computing Conference. Abstract
(2008).
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
(2013).
Embodied music listening and making in context-aware mobile applications: the EU-ICT SAME Project.
Gesture Workshop 2009..
(2009).
Expressive Irish Fiddle Performance Model Informed with Bowing.
International Computer Music Conference. Abstract
(2008).
A Framework for Performer Identification in Audio Recordings.
International Workshop on Machine Learning and Music - ECML-PKDD 09. Abstract
(2009).
Gesture sampling for instrumental sound synthesis: violin bowing as a case study.
International Computer Music Conference. Abstract
(2010).
A hair ribbon deflection model for low-intrusiveness measurement of bow force in violin performance..
New Interfaces for Musical Creation (NIME 2011). Abstract
(2011).
Identifying saxophonists from their playing styles.
30th AES Conference. Abstract
(2007).
Inducing rules of ensemble music performance: a machine learning approach.
3rd international conference on Music & Emotion, Jyväskylä.
(2013).
Intra-note Features Prediction Model for Jazz Saxophone Performance.
International Computer Music Conference. Abstract
(2005).
Investigating the relationship between expressivity and synchronization in ensemble performance: an exploratory study.
International Symposium on Performance Science, Vienna.
(2013).
A machine learning approach to expressive performance in jazz standards.
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Abstract
(2004).
(2011).