An expert system for harmonizing chorales in the style of J. S. Bach
Journal of Logic Programming - Logic programming applications
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Maximum Entropy Markov Models for Information Extraction and Segmentation
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Machine Learning for Sequential Data: A Review
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Training conditional random fields via gradient tree boosting
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Gaussian process classification for segmenting and annotating sequences
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Algorithms for Chordal Analysis
Computer Music Journal
Functional Harmonic Analysis Using Probabilistic Models
Computer Music Journal
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
The Cognition of Basic Musical Structures
The Cognition of Basic Musical Structures
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers
Proceedings of the 24th international conference on Machine learning
Tonal Harmony Analysis: A Supervised Sequential Learning Approach
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
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Tonal harmony analysis is arguably one of the most sophisticated tasks that musicians deal with. It combines general knowledge with contextual cues, being ingrained with both faceted and evolving objects, such as musical language, execution style, or even taste. In the present work we introduce breve, a system for tonal analysis. breve automatically learns to analyse music using the recently developed framework of conditional models. The system is presented and assessed on a corpus of Western classical pieces from the 18th to the late 19th Centuries repertoire. The results are discussed and interesting issues in modeling this problem are drawn.