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ASME Press Select Proceedings
International Conference on Computer and Computer Intelligence (ICCCI 2011)
By
ISBN:
9780791859926
No. of Pages:
740
Publisher:
ASME Press
Publication date:
2011
eBook Chapter
50 A Machine Learning Approach to Expression Modeling for the Singing Voice
By
Maria-Cristina Marinescu
,
Maria-Cristina Marinescu
Department of Computer Science,
Universidad Carlos III de Madrid Leganes
, Spain
; mcristina@arcos.inf.uc3m.es
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Rafael Ramirez
Rafael Ramirez
Department of Information and Communication Systems,
Universitat Pompeu Fabra Barcelona
, Spain
; rafael.ramirez@upf.edu
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Page Count:
5
-
Published:2011
Citation
Marinescu, M, & Ramirez, R. "A Machine Learning Approach to Expression Modeling for the Singing Voice." International Conference on Computer and Computer Intelligence (ICCCI 2011). Ed. Xie, Y. ASME Press, 2011.
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This work investigates how opera singers manipulate timing in order to produce expressive performances that have common features but also bear a distinguishable personal style. We characterize performances not only relative to the score, but also consider the contribution of features extracted from the libretto. Our approach is based on applying machine learning to extract singer-specific patterns of expressive singing from performances by Josep Carreras and Placido Domingo. We compare and contrast some of these rules, and we draw analogies between them and some of the general expressive performance rules from existing literature.
Abstract
Key Words
1 Introduction
2. Related Work
3. Expressive Singing Voice Modeling
4. Results
5. Conclusion
References
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