Biblio

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Musevic, S. (2013).  Non-Stationary Sinusoidal Analysis. Department of Information and Communication Technologies. 210. Abstract
Musevic, S., & Bonada J. (2015).  Distribution Derivative Method for Generalised Sinusoid With Complex Amplitude Modulation. International Conference on Digital Audio Effects (DAFx-15).
application/pdf iconDistribution Derivative Method for Generalised Sinusoid With Complex Amplitude Modulation.pdf
Musevic, S. (2009).  Non-stationary sinusoidal analysis. Abstract
Musevic, S., & Bonada J. (2013).  Derivative Analysis of Complex Polynomial Amplitude, Complex Exponential with Exponential Damping. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). Abstract
Musevic, S., & Bonada J. (2010).  Comparison of non-stationary sinusoid estimation methods using reassignment and derivatives. Sound and Music Computing Conference. Abstract
Munday, J. (2017).  Interfaces for Improvising with a Jazz Melody Generation System. Abstract
Müller, M., & Serrà J. (2011).  Audio content-based music retrieval. Int. Soc. for Music Information Retrieval Conf. (ISMIR). Abstract
application/pdf icon2011_MuellerSerra_TutorialProposal-AudioRetrieval_ISMIR.pdf
Mostafavi, A., Laurier C., Herrera P., & Ras Z. W. (2011).  Tailored tagger: A personalized, adaptive music tagging system. Abstract
application/pdf iconMostafavi-ismir-2011.pdf
Morelli, F. (2013).  The bad and the good singer: query tuning analysis for audio to audio Query by Humming. Abstract
application/pdf iconFilippo-Morelli-Master-Thesis-2013.pdf
Mora, J., Gómez F., Gómez E., Escobar Borrego F., & Díaz-Báñez J. M. (2010).  Melodic Characterization and Similarity in A Cappella Flamenco Cantes. International Society for Music Information Retrieval Conference (ISMIR) . Abstract
application/pdf iconMelodyFlamenco-ISMIR2010.pdf
Mora, J., Gómez-Martin F., Gómez E., & Díaz-Báñez J. M. (2016).  Melodic Contour and Mid-Level Global Features Applied to the Analysis of Flamenco Cantes. Journal of New Music Research . Abstract
Mora, A. (2003).  Desenvolupament d'un entorn per a l'anàlisi, transformaciò i síntesi de sons usant la llibreria CLAM.
Monzo, C., Formiga L., Adell J., Mayor O., Bonada J., Janer J., et al. (2009).  Properly Using Speech Synthesis and Voice Transformation for Audiovisual Content Generation. (IBC, Ed.).International Broadcasting Conference (IBC2009). Abstract
Molina-Solana, M., Arcos J. L., & Gómez E. (2010).   Identifying violin performers by their expressive trends . Intelligent Data Analysis. 14(5), 555-571. Abstract
Molina-Solana, M., Arcos J. L., & Gómez E. (2008).  Learning Violinist's Expressive Trends . International Workshop on Machine Learning and Music, Held in conjunction with ICML/COLT/UAI 2008. Abstract
Molina-Solana, M., Arcos J. L., & Gómez E. (2008).  Using Expressive Trends For Identifying Violin Performers. International Conference on Music Information Retrieval. Abstract
Molina, P., Haro G. G., & Jordà S. (2011).  BeatJockey: A new tool for enhancing DJ skills. New Interfaces for Musical Expression (NIME). 288-291. Abstract
application/pdf iconG20-Molina.pdf
Molina, E. (2012).  Automatic scoring of singing voice based on melodic similarity measures. Abstract
application/pdf iconEmilio-Molina-Master-Thesis-2012.pdf
Molina, E., Barbancho I., Gómez E., Barbancho A. M., & Tardón L. J. (2013).  Fundamental frequency alignment vs note-based melodic similarity for singing voice assessment. 8th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
application/pdf iconSingingAssessment_ICASSP2013.pdf
Molina, P. (2010).  DJ Suport Agent Based on Audio Mosaicing: Enhancing DJ-Skills for People With or Without Them.. Abstract
Miron, M., Janer J., & Gómez E. (2017).  Generating data to train convolutional neural networks for classical music source separation. Proceedings of the 14th Sound and Music Computing Conference. 227-233.
Miron, M., Carabias-Orti J. J., & Janer J. (2015).  Improving score-informed source separation for classical music through note refinement. 16th International Society for Music Information Retrieval (ISMIR) Conference. Abstract
application/pdf iconImproving score-informed source separation for classical music through note refinement.pdf
Miron, M., & Slizovskaia O. (2017).  Convolutional neural networks for audio processing: starting pack. Pydata Barcelona.
Miron, M., Carabias-Orti J. J., Bosch J., Gómez E., & Janer J. (2016).  Score-Informed Source Separation for Multichannel Orchestral Recordings. Journal of Electrical and Computer Engineering. 2016, Abstract
application/pdf icon8363507.pdf
Miron, M. (2011).  Automatic Detection of Hindustani Talas. Abstract
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