Biblio

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Schedl, M., Gómez E., & Urbano J. (2014).  Music Information Retrieval: Recent Developments and Applications. Foundations and Trends in Information Retrieval. 8(2-3), 127-261. Abstract
application/pdf icon059-music-information-retrieval-recent-developments-applications.pdf
Schedl, M., Melenhorst M., Liem C., Martorell A., Mayor O., & Tkalčič M. (2016).  A personality-based adaptive system for visualizing classical music performances. 7th International Conference on Multimedia Systems (MMSys'16). Abstract
application/pdf iconA personality-based adaptive system for visualizing classical music performances
Schedl, M., Knees P., McFee B., Bogdanov D., & Kaminskas M. (2015).  Music Recommender Systems. Recommender Systems Handbook. 453-492. Abstract
Schedl, M., Eghbal-Zadeh H., Gómez E., & Tkalcic M. (2016).  An analysis of agreement in classical music perception and its relationship to listener characteristics. 17th International Society for Music Information Retrieval Conference (ISMIR 2016). 578-583. Abstract
Schedl, M., Gómez E., Trent E., Tkalcic M., Zadeh H. E., & Martorell A. (2017).  On the Interrelation between Listener Characteristics and the Perception of Emotion in Classical Orchestra Music. IEEE Transactions on Affective Computing. Abstract
Schedl, M., Stober S., Gómez E., Orio N., & Liem C. C. S. (2012).  User-Aware Music Retrieval. (Müller, M., Goto, M., Markus Schedl, Ed.).Multimodal Music Processing. 3, 135-156.
Schedl, M., Yang Y., & Herrera P. (2016).  Introduction to Intelligent Music Systems and Applications. ACM Transactions on Intelligent Systems and Applications. 8(2), 17:1-17:8.
Scarano, D. (2016).  Automatic Classification of Musical Instrument Samples. Abstract
application/pdf iconDaniele-Scarano-Master-thesis-2016.pdf
Sarasúa, Á., Melenhorst M., Julià C. F., & Gómez E. (2016).  Becoming the Maestro - A Game to Enhance Curiosity for Classical Music. 2016 8th International Conference on Games and Virtual Worlds for Serious Applications (VS-GAMES). 1-4.
Sarasúa, Á., Laurier C., & Herrera P. (2012).  Support Vector Machine Active Learning for Music Mood Tagging. 9th International Symposium on Computer Music Modeling and Retrieval (CMMR).
application/pdf iconsarasúa-CMMR-2012.pdf
Sarasua, A., Urbano J., & Gomez E. (2019).  Mapping by Observation: Building a User-Tailored Conducting System From Spontaneous Movements. Frontiers on Digital Humanities. Abstract
Sarasúa, Á., Caramiaux B., & Tanaka A. (2016).  Machine Learning of Personal Gesture Variation in Music Conducting. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. 3428–3432.
Sarasúa, Á. (2011).  Active Learning for User-Tailored Refined Music Mood Detection. Abstract
application/pdf iconSarasua-Alvaro-Master-thesis-2011.pdf
Sarasúa, Á., & Guaus E. (2014).  Beat Tracking from Conducting Gestural Data: A Multi-Subject Study. Proceedings of the 2014 International Workshop on Movement and Computing. 118–123. Abstract
application/pdf iconmoco-ready.pdf
Sarasúa, Á. (2017).  Musical Interaction Based on the Conductor Metaphor. Department of Information and Communication Technologies. Abstract
de los Santos, C. A. (2010).  Nonlinear Audio Recurrence Analysis with Application to Music Genre Classification. Abstract
Sandvold, V., Aussenac T., Celma Ò., & Herrera P. (2006).  Good Vibrations: Music Discovery through Personal Musical Concepts. 7th International Conference on Music Information Retrieval (ISMIR). Abstract
Sandvold, V., & Herrera P. (2005).  Towards a Semantic Descriptor of Subjective Intensity in Music. International Computer Music Conference. Abstract
Sandvold, V., Gouyon F., & Herrera P. (2004).  Percussion Classification in polyphonic audio recordings using localized sound models. 5th International Conference on Music Information Retrieval (ISMIR'04). Abstract
Sánchez-Mendoza, D. (2005).  Emulating Electric Guitar Effects With Neural Networks. Abstract
San Agustín, A. (2008).  Design and implementation of new communication channels between public and an artistic performance. Abstract
Salselas, I., & Herrera P. (2011).  Music and speech in early development: automatic analysis and classification of prosodic features from two Portuguese variants. Journal of Portuguese Linguistics. 9/10, 11-36. Abstract
Salselas, I. (2013).  Exploring interactions between music and language during the early development of music cognition. A computational modelling approach. Department of Information and Communication Technologies. 137. Abstract
Salselas, I., Hazan A., Herrera P., & Purwins H. (2008).  The Development of Melodic Representations at Early Age: Towards a Computational Model.. Music, Language and the Mind 2008. Abstract
Salselas, I., & Herrera P. (2010).  Development of Perception and Representation of Rhythmic Information: Towards a Computational Model. 2010 IEEE 9th International Conference on Development and Learning. Abstract
application/pdf iconDevelopment of Perception and Representation of Rhythmic Information.pdf
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