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).
Modeling musical articulation gestures in singing voice performances.
AES 121th Convention. Abstract
(2006).
Modelling Expressive Performance A Regression Tree Approach Based on Strongly Typed Genetic Programming.
European Workshop on Evolutionary Music and Art. Abstract
(2006).
A Sequential Covering Evolutionary Algorithm for Expressive Music Performance.
Conference on Innovative Applications of Artificial Intelligence. Abstract
(2006).
Using concatenative synthesis for expressive performance in jazz saxophone.
International Computer Music Conference. Abstract
(2006).
(2005).
Discovering Expressive Transformation Rules from Saxophone Jazz Performances.
Journal of New Music Research. 34, 319-330. Abstract
(2005).
Intra-note Features Prediction Model for Jazz Saxophone Performance.
International Computer Music Conference. Abstract
(2005).
A machine learning approach to expressive performance in jazz standards.
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Abstract
(2004).
Understanding expressive transformations in saxophone jazz performances using inductive machine learning.
Sound and Music Computing Conference. Abstract
(2004). - « first
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