Browsing by Author "Giraldo, Sergio"

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  • Giraldo, Sergio; Ramírez, Rafael,1966- (Frontiers, 2016)
    Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance ...
  • Ramírez, Rafael,1966-; Giraldo, Sergio (Taylor & Francis, 2016)
    We present a machine learning approach to automatically generate expressive (ornamented) jazz performances from un-expressive music scores. Features extracted from the scores and the corresponding audio recordings performed ...
  • Giraldo, Sergio; Ramírez, Rafael,1966-; Waddell, George; Williamon, Aaron (Machine Learning and Music (MML), 2017)
    The assessment of the sound properties of a performed mu- sical note has been widely studied in the past. Although a consensus exist on what is a good or a bad musical performance, there is not a formal de nition of ...
  • Giraldo, Sergio; Waddell, George; Nou Plana, Ignasi; Ortega, Ariadna; Mayor, Oscar; Perez, Alfonso; Williamon, Aaron; Ramírez, Rafael,1966- (Frontiers, 2019)
    The automatic assessment of music performance has become an area of increasing interest due to the growing number of technology-enhanced music learning systems. In most of these systems, the assessment of musical performance ...
  • Giraldo, Sergio; Ortega, Ariadna; Pérez Carrillo, Alfonso Antonio, 1977-; Ramírez, Rafael,1966-; Waddell, George; Williamon, Aaron (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    The automatic assessment of music performance has become an area of special interest due to the increasing amount of technology-enhanced music learning systems. However, in most of these systems the assessment of the musical ...
  • Ortega, Fabio J. M.; Giraldo, Sergio; Ramírez, Rafael,1966- (ACM Association for Computer Machinery, 2017)
    Though musicians tend to agree on the importance of practicing expressivity in performance, not many tools and techniques are available for the task. A machine learning model is proposed for predicting bowing velocity ...
  • Siquier, Marc; Giraldo, Sergio; Ramírez, Rafael,1966- (Machine Learning and Music (MML), 2017)
    Computational modelling of expressive music performance has been widely studied in the past. While previous work in this area has been mainly focused on classical piano music, there has been very little work on guitar ...
  • Giraldo, Sergio (Universitat Pompeu Fabra, 2016-09-16)
    Computational modelling of expressive music performance deals with the analysis and characterization of performance deviations from the score that a musician may introduce when playing a piece in order to add expression. ...
  • Giraldo, Sergio; Ramírez, Rafael,1966-; Waddell, George; Williamon, Aaron (McGill University, 2018)
    Automatic assessment of music performance is an open research area widely studied in the past. A vast amount of systems aiming to enhance the learning process of a musical instrument are being developed in the recent years. ...
  • Ramírez, Rafael,1966-; Canepa, Corrado; Ghisio, Simone; Kolykhalova, Ksenia; Mancini, Maurizio; Volta, Erica; Volpe, Gualtiero; Giraldo, Sergio; Mayor, Oscar; Perez, Alfonso; Waddell, George; Williamon, Aaron (ACM Association for Computer Machinery, 2018)
    Learning to play a musical instrument is a difficult task, requiring the development of sophisticated skills. Nowadays, such a learning process is mostly based on the master-apprentice model. Technologies are rarely ...
  • Angulo, Iñigo; Giraldo, Sergio; Ramírez, Rafael,1966- (Anglia Ruskin University, 2016)
    Music representation has been a widely researched topic through centuries. Transcription of music through the conventional notation system has dominated the field, for the best part of the last centuries. However, this ...
  • Kitahara, Tetsuro; Giraldo, Sergio; Ramírez, Rafael,1966- (Aalborg University Copenhagen, 2017)
    In this paper, we present JamSketch, a real-time improvisation support system which automatically generates melodies according to melodic outlines drawn by the users. The system generates the improvised melodies based on ...
  • Bantula, Helena; Giraldo, Sergio; Ramírez, Rafael,1966- (International Society for Music Information Retrieval (ISMIR), 2016)
    Computational expressive music performance studies the analysis and characterisation of the deviations that a musician introduces when performing a musical piece. It has been studied in a classical context where timing and ...
  • Ramírez, Rafael,1966-; Palencia-Lefler Ors, Manuel; Giraldo, Sergio; Vamvakousis, Zacharias (Frontiers, 2015)
    We introduce a new neurofeedback approach, which allows users to manipulate expressive parameters in music performances using their emotional state, and we present the results of a pilot clinical experiment applying the ...
  • Ortega, Fabio J. M.; Giraldo, Sergio; Pérez Carrillo, Alfonso Antonio, 1977-; Ramírez, Rafael,1966- (Frontiers, 2019)
    Background: Expression is a key skill in music performance, and one that is difficult to address in music lessons. Computational models that learn from expert performances can help providing suggestions and feedback to ...
  • Ortega, Fabio J. M.; Giraldo, Sergio; Ramírez, Rafael,1966- (Machine Learning and Music (MML), 2017)
    A model is proposed for predicting expressive variations in dynamics for violin performances with the purpose of facilitating expressive performance learning by students. The model uses phrases rather than single notes as ...