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Conception des modèles d'observation audio temps réel à l ... - atiam

Conception des modèles d'observation audio temps réel à l ... - atiam

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Bibliographie[1] Avrim Blum and Pat Langley. Selection of relevant features andexamples in machine learning. Artificial Intelligence, 97(1-2) :245–271,1997.[2] Arshia Cont. Improvement of observation modeling for score following.Dea <strong>atiam</strong>, University of Paris 6, IRCAM, Paris, 2004.[3] Arshia Cont. Realtime <strong>audio</strong> to score alignment for polyphonic musicinstruments using sparse non-negative constraints and hierarchicalhmms. In IEEE International Conference in Acoustics and Speech Signal Processing(ICASSP). Toulouse, May 2006.[4] Arshia Cont, Diemo Schwarz, and Norbert Schnell. Training ircam’sscore follower. In IEEE International Conference on Acoustics and SpeechSignal Processing (ICASSP). Philadelphia, March 2005.[5] Corinna Cortes and Mehryar Mohri. Auc optimization vs. error rateminimization, 2003.[6] R. B. Dannenberg. An on-line algorithm for real-time accompaniment.In Proc. of the 1984 Int. Computer Music Conf., pages 193–198. ComputerMusic Association, June 1984.[7] Arthur Dempster, Nan Laird, and Donald Rubin. Maximum likelihoodfrom incomplete data via the em algorithm, 1977.[8] Bruce Draper, Carol Kaito, and José Bins. Iterative relief, 2003.[9] S. Essid, P. Leveau, G. Richard, L. Daudet, and B. David. On the usefulnessof differentiated transient/steady-state processing in machine recognitionof musical instruments. In Proc. AES 118th Convention, Barcelona,Spain, May 2005.[10] Slim Essid. Classification automatique de signaux <strong>audio</strong>-fréquences : reconnaissance<strong>des</strong> instruments de musique. PhD thesis, ENST, 2006.[11] David E. Goldberg. Genetic algorithms in search, optimization and machinelearning. Addison-Wesley, 1989.[12] Isabelle Guyon and André Elisseeff. An introduction to variable andfeature selection. J. Mach. Learn. Res., 3 :1157–1182, 2003.

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