Biblio

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Ganguli, K. K., Lele A., Pinjani S., Rao P., Srinivasamurthy A., & Gulati S. (2017).  Melodic Shape Stylization for Robust and Efficient Motif Detection in Hindustani Vocal Music. National Conference for Communications. Abstract
application/pdf iconGanguli-et-al-NCC-2017.pdf
Gulati, S., Serrà J., Ishwar V., & Serra X. (2014).  Melodic Pattern Extraction in Large Collections of Music Recordings Using Time Series Mining Techniques. International Society for Music Information Retrieval Conference (Late breaking demo). Abstract
application/pdf iconPoster
Gómez, E. (2002).  Melodic Description of Audio Signals for Music Content Processing. Abstract
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
Gómez, E., Grachten M., Amatriain X., & Arcos J. L. (2003).  Melodic characterization of monophonic recordings for expressive tempo transformations. Abstract
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
Bogdanov, D., Porter A., Urbano J., & Schreiber H. (2018).  The MediaEval 2018 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources. MediaEval 2018 Workshop. Abstract
Oramas, S., Bogdanov D., & Porter A. (2018).  MediaEval 2018 AcousticBrainz Genre Task: A baseline combining deep feature embeddings across datasets. MediaEval 2018 Workshop.
Bogdanov, D., Porter A., Urbano J., & Schreiber H. (2017).  The MediaEval 2017 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources. MediaEval 2017 Workshop. Abstract
Pérez, A., Bonada J., Maestre E., Guaus E., & Blaauw M. (2008).  Measuring Violin Sound Radiation for Sound Equalization . Acoustics08. Abstract
Serrà, J., Corral A., Boguñá M., Haro G. G., & Arcos J. L. (2012).  Measuring the evolution of contemporary western popular music. Scientific Reports. 2(521),  Abstract
Guaus, E., Bonada J., Pérez A., Maestre E., & Blaauw M. (2007).  Measuring the bow pressing force in a real violin performance. International Symposium on Musical Acoustics. Abstract
Valero, J. J. (2013).  Measuring Similarity of Automatically Extracted Melodic Pitch Contours for Audio-based Query by Humming of Polyphonic Music Collections. Abstract
Guastavino, C., Gómez F., Toussaint G., Marandola F., & Gómez E. (2009).  Measuring Similarity between Flamenco Rhythmic Patterns. Journal of New Music Research. 38(2), 129-138. Abstract
application/pdf iconGuastavinoEtAlJNMR2009.pdf
Troes, T. (2017).  Measuring groove: A Computational Analysis of Timing and Dynamics in Drum Recordings. Abstract
Papiotis, P., Marchini M., Maestre E., & Pérez A. (2011).  Measuring ensemble synchrony through violin performance parameters: a preliminary progress report. 2nd Workshop of Social Behavior in Music (SBM-2011/INTETAIN-2011). Abstract
application/pdf iconSBM2011_cameraready.pdf
Papiotis, P., Marchini M., Perez A., & Maestre E. (2014).  Measuring ensemble interdependence in a string quartet through analysis of multidimensional performance data. Frontiers in Psychology. 5, Abstract
Nieves, S. (2019).  Measurement of the Impulse Response of the Guitar to Extract Timbre Features. Abstract
Mateo Presser, A. (2011).  Measurement of Car Audio Sound Quality using Audio Content Features. Abstract
Plata Rueda, Á. (2015).  Measurement and computational model of the maximum stable gain in acoustic feedback scenarios. Abstract
application/pdf iconAngel-Plata-Master-thesis-2015.pdf
Jordà, S., & Alonso M. (2006).  Mary had a little scoreTable* or the reacTable* goes melodic. New Interfaces for Musical Expression (NIME). Abstract
Kaltenbrunner, M., & Huxor A. (2001).  Marvin Supporting Awareness through Audio in Collaborative Virtual Environments. Abstract
Janer, J., & Maestre E. (2008).  Mapping phonetic features for voice-driven sound synthesis. eBusiness and Telecommunication Networks. CCIS Series. Abstract
Sarasua, A., Urbano J., & Gomez E. (2019).  Mapping by Observation: Building a User-Tailored Conducting System From Spontaneous Movements. Frontiers on Digital Humanities. Abstract
Vinceslas, L., Garcia F., Pérez A., & Maestre E. (2011).  Mapping Blowing Pressure and Sound Features in Recorder Playing. DAFX. 357-360. Abstract
application/pdf icon37_e.pdf
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