Biblio

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Ramesh, A. (2009).  Singing Voice Nasality Detection in Polyphonic Audio. Abstract
Ramires, A., & Serra X. (2019).  Data augmentation for instrument classification robust to audio effects. 22nd International Conference on Digital Audio Effects (DAFx-19). Abstract
Ramirez, R. (2004).  Inductive Logic Programming and Music.
Ramirez, R., Maestre E., Pertusa A., Gómez E., & Serra X. (2007).  Performance-based Interpreter Identification in Saxophone Audio Recordings. IEEE Transactions on Circuits and Systems for Video Technology. 17, 356-364. Abstract
Ramirez, R., Pérez A., Kersten S., & Rizo D. (2010).  Modeling Violin Performances Using Inductive Logic Programming. Intelligent Data Analysis.
Ramirez, R., Hazan A., & Maestre E. (2005).  Intra-note Features Prediction Model for Jazz Saxophone Performance. International Computer Music Conference. Abstract
Ramírez, M. (2002).  CLAM Visualization Module Disseny d'un mòdul de visualització OO per a un entorn de processament d'àudio independent de plataforma. Abstract
Ramírez, M., Martinez J., & Santosa A. (2004).  Constraint-based synchronization and verification of distributed Java programs. Lecture Notes in Computer Science . 3132, Abstract
Ramirez, R. (2008).  An fMRI Study on Attentive Music Listening. The Neurosciences and Music. Abstract
Ramirez, R., Palencia M., Giraldo S., & Vamvakousis Z. (2015).  Musical neurofeedback for treating depression in elderly people. Frontiers in Neuroscience. 9(354), 
application/pdf iconFrontiersHumNeuFINAL.pdf
Ramirez, R., & Hazan A. (2005).  Understanding expressive music performance using genetic algorithms. Lecture Notes in Computer Science 3449. Abstract
Ramirez, R., Maestre E., & Serra X. (2012).  A Rule-Based Evolutionary Approach to Music Performance Modeling. IEEE Transactions on Evolutionary Computation. 16(1), 96 - 107. Abstract
Ramirez, R., Maestre E., & Pertusa A. (2007).  Identifying saxophonists from their playing styles. 30th AES Conference. Abstract
Ramirez, R., Maestre E., & Serra X. (2010).  Automatic performer identification in commercial monophonic Jazz performances. Pattern Recognition Letters. 31(12), 1514-1523.
Ramirez, R., Hazan A., Maestre E., & Serra X. (2006).  A Machine Learning Approach to Expressive Performance in Jazz Standards. (Petrushin, V. A., Khan, L., Ed.).Multimedia Data Mining and Knowledge Discovery. Abstract
Ramirez, R., Hazan A., Gómez E., Maestre E., & Serra X. (2005).  Discovering Expressive Transformation Rules from Saxophone Jazz Performances. Journal of New Music Research. 34, 319-330. Abstract
Ramirez, R., & Maestre E. (2009).  A Framework for Performer Identification in Audio Recordings. International Workshop on Machine Learning and Music - ECML-PKDD 09. Abstract
Ramirez, R., & Hazan A. (2004).  Rule induction for expressive music performance modeling. Abstract
Ramirez, R., Gómez E., Vicente V., Puiggròs M., Hazan A., & Maestre E. (2006).  Modeling Expressive Music Performance in Bassoon Audio Recordings. Intelligent Computing in Signal Processing and Pattern Recognition. 345, 951-957.
Ramirez, R., & Hazan A. (2005).  Modeling expressive music performance in jazz. International Florida Artificial Intelligence Research Society Conference. Abstract
Ramirez, R., Hazan A., Maestre E., & Serra X. (2008).  A Genetic Rule-based Expressive Performance Model for Jazz Saxophone. Computer Music Journal. 32, 38-50. Abstract
Ramirez, R., Maestre E., Pérez A., & Serra X. (2011).  Automatic Performer Identification in Celtic Violin Audio Recordings. Journal of New Music Research. 40(2), 165-174. Abstract
Ramirez, R., Hazan A., Gómez E., & Maestre E. (2004).  Understanding expressive transformations in saxophone jazz performances using inductive machine learning. Sound and Music Computing Conference. Abstract
Ramirez, R., Hazan A., & Maestre E. (2006).  A Sequential Covering Evolutionary Algorithm for Expressive Music Performance. Conference on Innovative Applications of Artificial Intelligence. Abstract
Ramirez, R., & Hazan A. (2004).  Learning Expressive Performance Rules in Jazz.
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