Foundations of computer music
IEEE Transactions on Pattern Analysis and Machine Intelligence
Guest Editor's Introduction: Computer-Generated Music
Computer - Special issue: Computer-generated music
Machine models of music
Statistical methods for speech recognition
Statistical methods for speech recognition
MIDI Systems and Control
Speech Recognition and Coding: New Advances and Trends
Speech Recognition and Coding: New Advances and Trends
Proceedings of the Second International Colloquium on Grammatical Inference and Applications
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Learning Regular Grammars to Model Musical Style: Comparing Different Coding Schemes
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
Two Different Approaches for Cost-Efficient Viterbi Parsing with Error Correction
SSPR '96 Proceedings of the 6th International Workshop on Advances in Structural and Syntactical Pattern Recognition
Representation and Discovery of Vertical Patterns in Music
ICMAI '02 Proceedings of the Second International Conference on Music and Artificial Intelligence
Robust Polyphonic Music Retrieval with N-grams
Journal of Intelligent Information Systems
Classification of Melodies by Composer with Hidden Markov Models
WEDELMUSIC '01 Proceedings of the First International Conference on WEB Delivering of Music (WEDELMUSIC'01)
Probabilistic Finite-State Machines-Part II
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Cognition of Basic Musical Structures
The Cognition of Basic Musical Structures
A unified model of structural organization in language and music
Journal of Artificial Intelligence Research
A text categorization approach for music style recognition
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Learning stochastic finite automata for musical style recognition
CIAA'05 Proceedings of the 10th international conference on Implementation and Application of Automata
Musical Style Identification with n-Grams and Neural Networks
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Graph-Based Representation of Symbolic Musical Data
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
Genre classification of music by tonal harmony
Intelligent Data Analysis - Machine Learning and Music
Classification accuracy is not enough
Journal of Intelligent Information Systems
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This article reviews our work in the field of music processing (MP) using grammatical inference (GI), where regular grammars are used for modeling musical style. These models can be used to generate automatic composition (AC) and classify music by style (musical style identification) with their resulting applications. The latter, for instance, would improve content-based retrieval in multimedia databases, joining indexing by musical style to other suitable indexes. In this work, several GI techniques are used to learn from examples of melodies, stochastic grammars for different musical styles. Then, each of the learned grammars is used to generate new melodies (composition) or to classify test melodies (style identification). Our studies in this field show the need of proper music coding schemes, so different coding schemes are presented and compared. Results from our previous studies have been improved, achieving in style identification a classification error rate that ranges from 0.5 to 1.7%, depending on the corpus used.