Biblio
Filters: Author is Hazan, A. [Clear All Filters]
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).
An Approach to Expressive Music Performance Modeling.
118th Audio Engineering Society Convention. Abstract
(2005).
Billaboop real-time voice-driven drum generator.
118th Audio Engineering Society Convention. Abstract
(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).
Modeling expressive music performance in jazz.
International Florida Artificial Intelligence Research Society Conference. Abstract
(2005).
Understanding expressive music performance using genetic algorithms.
Lecture Notes in Computer Science 3449. Abstract
(2005).
(2006).
(2006).
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).
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).
A Tool for Generating and Explaining Expressive Music Performances of Monophonic Jazz Melodies.
International Journal on Artificial Intelligence Tools. 15, 673-691. Abstract
(2006).
Using concatenative synthesis for expressive performance in jazz saxophone.
International Computer Music Conference. Abstract
(2006).
Attention as musical interplay of bottom-up accents and expectation.
GOSPEL Workshop. Abstract
(2007).
Computational Modeling of Statistical Learning of Tone Sequences (Poster).
International Conference on Cognitive and Neural Systems (ICCNS 2007). Abstract
(2007).
Dynamical Hierarchical Self-Organization of Harmonic, Motivic, and Pitch Categories .
Music, Brain and Cognition. Part 2: Models of Sound and Cognition, held at NIPS). Abstract
(2007).
Expectation Along The Beat A Use Case For Music Expectation Models.
International Computer Music Conference. Abstract
(2007).