Biblio

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Mealla, S. (2012).  Brain Tangible Interfaces for Multimodal Rehabilitation. Human Computer Confluence Summer School.
application/pdf iconHC2SS_mealla.pdf
Mealla, S. (2010).  Effects of Physiology-Based Interaction on Collaborative Performance. Abstract
Mealla, S., Oliveira A., Marimon X., Steffert T., Jordà S., & Väljamäe A. (2014).  The Role of Personalization and Multiple EEG and Sound Features Selection in Real Time Sonification for Neurofeedback. International Conference on Physiological Computing Systems.
application/pdf iconMealla37_PhyCS_camera_ready.pdf
Mealla, S., Jordà S., & Väljamäe A. (2016).  Physiopucks: Increasing User Motivation by Combining Tangible and Implicit Physiological interaction. Transactions on Computer-Human Interaction (TOCHI). 23(1),  Abstract
Mealla, S., Väljamäe A., Bosi M., & Jordà S. (2011).  Sonification of Brain and Body Signals in Collaborative Tasks Using a Tabletop Musical Interface. International Conference on Auditory Display (ICAD). Abstract
application/pdf iconbrain_and_body_sonif_camera_ready.pdf
Mealla, S., Väljamäe A., Bosi M., & Jordà S. (2011).  Let Me Listen to Your Brain: Physiology-based Interaction in Collaborative Music Composition. Brain and Body Interfaces Workshop. ACM CHI Conference on Human Factors in Computing Systems. Abstract
application/pdf iconCHI2011_mealla.pdf
Meléndez, B. (2016).  Studying the Application of Deep Learning to the Task of Key Estimation. Abstract
Meléndez-Catalán, B., Molina E., & Gómez E. (2019).  Open Broadcast Media Audio from TV: A Dataset of TV Broadcast Audio with Relative Music Loudness Annotations. Transactions of the International Society for Music Information Retrieval (TISMIR). 2(1), 43-51. Abstract
Meléndez-Catalán, B., Molina E., & Gómez E. (2017).  BAT: An open-source, web-based audio events annotation tool. Web Audio Conference. Abstract
Melenhorst, M., van der Sterren R., Arzt A., Martorell A., & C. S. Liem C. (2015).  A tablet app to enrich the live and post-live experience of classical concerts. 3rd International Workshop on Interactive Content Consumption. Abstract
application/pdf iconA tablet app to enrich the live and post-live experience of classical concerts.pdf
Melidis, P. (2012).  Electronic Music Artist Identification. Abstract
Merchán, F. (2008).  Expressive characterization of flamenco singing. Abstract
Meseguer, G. (2013).  Automatic content-based detection of influences in the history of Progressive Rock Music. Abstract
application/pdf iconGabriel-Meseguer-Master-Thesis-2013.pdf
Mimilakis, S. I. (2014).  Voice Quality Modelling with the Wide-Band Harmonic Sinusoidal Modelling Algorithm. Abstract
application/pdf iconStylianos-Ioannis-Mimilakis-Master-Thesis-2014.pdf
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
Miron, M. (2018).  Source Separation Methods for Orchestral Music: Timbre-Informed and Score-Informed Strategies. Department of Information and Communication Technologies. 299. Abstract
Miron, M., Carabias-Orti J. J., & Janer J. (2014).  Audio-to-score alignment at the note level for orchestral recordings. 15th International Society for Music Information Retrieval Conference.
application/pdf iconMironCarabiasJaner2014.pdf
Miron, M., Janer J., & Gómez E. (2017).  Monaural score-informed source separation for classical music using convolutional neural networks. 18th International Society for Music Information Retrieval Conference.
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.
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
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