Biblio

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1998
Wright, M., Chaudhary A., Freed A., Wessel D., Rodet X., Woehrmann R., et al. (1998).  New Applications of the Sound Description Interchange Format. International Computer Music Conference. Abstract
2000
Purwins, H., Blankertz B., & Obermayer K. (2000).  A new method for tracking modulations in tonal music in audio data format. International Joint Conference on Neural Network (IJCNN'00). 6, 270-275. Abstract
2001
Jordà, S. (2001).  New Musical Interfaces and New Music-making Paradigms. Abstract
2004
Cano, P., Koppenberger M., Le Groux S., Ricard J., Herrera P., & Wack N. (2004).  Nearest-neighbor generic sound classification with a wordnet-based taxonomy. Abstract
Guaus, E. (2004).  New approaches for rhythmic description of audio signals. Abstract
Guaus, E., & Batlle E. (2004).  A non-linear rhythm-based style classifcation for Broadcast Speech-Music Discrimination. 116th AES Convention. Abstract
2005
G. Mahedero, J., Cano P., Martinez A., Gouyon F., & Koppenberger M. (2005).  Natural language processing of lyrics. Abstract
Barbosa, A., Cardoso J., & Geiger G. (2005).  Network Latency Adaptive Tempo in the Public Sound Objects System. Abstract
Cano, P., Koppenberger M., Le Groux S., Ricard J., Wack N., & Herrera P. (2005).  Nearest-Neighbor Automatic Sound Classification with a WordNet Taxonomy. Journal of Intelligent Information Systems. 24, 99-111. Abstract
2007
Jensenius, A., Camurri A., Castagné N., Maestre E., Malloch J., McGilvray D., et al. (2007).  The need of formats for streaming and storing music-related movement and gesture data. Abstract
2008
G. Risueño, M. (2008).  NAUTILUS. A Musical, Collaborative and Interactive Sonification Toolkit. Abstract
Chen, G., Wang T. - G., & Herrera P. (2008).  A Novel Music Retrieval System with Relevance Feedback. Third International Conference on Innovative Computing, Information and Control. Abstract
Celma, Ò., & Herrera P. (2008).  A New Approach to Evaluating Novel Recommendations. 2008 ACM Conference on Recommender Systems. Abstract
application/pdf iconpostprint version
2009
Musevic, S. (2009).  Non-stationary sinusoidal analysis. Abstract
2010
de los Santos, C. A. (2010).  Nonlinear Audio Recurrence Analysis with Application to Music Genre Classification. Abstract
2011
Serrà, J., de los Santos C. A., & Andrzejak R. G. (2011).  Nonlinear audio recurrence analysis with application to genre classification. IEEE International Conference on Acoustics, Speech and Signal processing (ICASSP). 169-172. Abstract
application/pdf iconserraetal_icassp2011.pdf
2012
Unal, E., Bozkurt B., & Karaosmanoglu K. M. (2012).  N-gram based Statistical Makam Detection on Makam Music in Turkey using Symbolic Data. Int. Soc. for Music Information Retrieval Conf. (ISMIR).
application/pdf icon2012_4_Ismir_Unal_etAl.pdf
Bucci, A., Pérez A., & Bonada J. (2012).  Non-Impulsive Signal Deconvolution for Computation of Violin Impulse Responses. IEEE International Conference on Acoustics, Speech, and Signal Processing. Abstract
application/pdf iconDeconvolution.pdf
2013
Musevic, S. (2013).  Non-Stationary Sinusoidal Analysis. Department of Information and Communication Technologies. 210. Abstract
Carabias-Orti, J. J., Cobos M., Vera-Candeas P., & Rodríguez-Serrano F. J. (2013).  Nonnegative signal factorization with learnt instrument models for sound source separation in close-microphone recordings. EURASIP Journal on Advances in Signal Processing. Abstract
2014
Romaní Picas, O. (2014).  A novel audio-to-score alignment method using velocity-driven DTW. Abstract
2016
Patlatzoglou, K. (2016).  Neural and Music Correlates of Music-evoked Emotions. Abstract
Caro Repetto, R., & Serra X. (2016).  NACTA: construyendo el futuro de la tradición del jingju. Itinerarios, Espacios, Contextos: XIV congreso de la Sociedad de Etnomusicología, IX congreso de IASPM España. Abstract
application/pdf iconCaro & Serra - NACTA y jingju - SIBE 2017 (presentation slides)
2017
Delgado, N. (2017).  Neural Correlates of Music and Emotion in ASD and Typical Children. Abstract
Blanco, A. D., & Ramirez R. (2017).  Neural correlates of bow learning technique. Proceedings of the 10th International Workshop on Machine Learning and Music. 1-6. Abstract
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