A Lyrics-matching QBH System for Interactive Environments

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A computational approach to studying interdependence in string quartet performance

This dissertation proposes a computational data-driven methodology to measure music ensemble interdependence - the degree to which musicians interact and influence each other’s actions in order to achieve a shared goal - using a string quartet ensemble as a case study. Combining elements from multiple disciplines, this methodology involves the acquisition of multimodal performance data under experimental conditions, the extraction of numerical features that describe the performance in terms of distinct musical dimensions (intonation, dynamics, timbre, timing), the computational estimation of interdependence for each performance dimension individually, and the assessment of the capability of listeners to perceive interdependence. Our results show that it is possible to detect interdependence in string quartet performance in different performance dimensions, as well as to compare its relative amount across different recordings and relate the results to the underlying goal of the score. The experimental data have been published online as an open research dataset.Esta disertación propone una metodología computacional basada en datos para medir la interdependencia entre los intérpretes de un conjunto musical - el grado en que los musicos interactuán e influyen sus acciones para conseguir un objetivo común - utilizando un cuarteto de cuerda como caso de estudio. Esta metodología implica la adquisición de datos multimodales de interpretaciones bajo condiciones experimentales, la extracción de descriptores numéricos que describen la interpretación en términos de distintas dimensiones musicales (entonación, dinámica, timbre, tempo), la estimación computacional de la interdependencia de cada dimensión individualmente y la evaluación de la capacidad de oyentes para percibir la interdependencia. Nuestros resultados muestran que es posible detectar la interdependencia en distintas dimensiones de interpretación, así como comparar su peso relativo a través de distintas grabaciones y relacionar los resultados con el objetivo fundamental de la partitura. Los datos experimentales han sido publicados online en forma de base de datos abierta para la investigación

Investigating the relationship between expressivity and synchronization in ensemble performance: an exploratory study

Comunicació presentada al International Symposium on Performance Science (ISPS), celebrat a Viena (Àustria) els dies 28 a 31 d'agost de 2013.We present an exploratory study on ensemble expressive performance based on the analysis of string quartet recordings. We recorded a piece with three expressive intentions: mechanical, normal, and exaggerated. We made use of bowing gesture data (bow velocity and force) acquired through a motion tracking system to devise a precise score performance alignment. Individual contact microphone audio signals allowed extraction of a set of audio descriptors for each musician and each note. We show how tempo and loudness on a macro-scale changed across expressive intentions and score sections. The score is also taken into account in the analysis by extracting contextual attributes for each note. We show that micro-deviations were affected by note contextual attributes, whereas the effect of expressive intention varied across sections. We find sections that exhibited a lower entrainment, where individual parts tended to be freer and presented more asynchronies.This work was supported by EU FET-Open SIEMPRE and by SIEMPRE-MAS4

Timing synchronization in string quartet performance: a preliminary study

This work presents a preliminary study of timing synchronization/nphenomena in string quartet performance. Accurate timing information/nextracted from real recordings is used to compare timing deviations/nin solo and ensemble performance when executing a simple musical/npassage. Multi-modal data is acquired from real performance and/nprocessed towards obtaining note-level segmentation of recorded performances./nFrom such segmentation, a series of timing deviation analyses/nare carried out at two different temporal levels, focusing on the exploration/nof significant differences between solo and ensemble performances./nThis paper briefly introduces, via an initial exploratory study, the experimental/nframework on which further, more complete analyses are to be/ncarried out with the aim of observing and describing certain synchronization/nphenomena taking place in ensemble music making.Papiotis, Panagioti

Multidimensional analysis of interdependence in a string quartet

Comunicació presentada al International Symposium on Performance Science (ISPS), celebrat a Viena (Àustria) els dies 28 a 31 d'agost de 2013.In a musical ensemble such as a string quartet, the performers can influence each other’s actions in several aspects of the performance simultaneously. Based on a set of recorded string quartet exercises, we carried out a quantitative analysis of ensemble interdependence in four distinct dimensions of the performance: dynamics, intonation, tempo, and timbre. We investigated the fluctuations of interdependence across these four dimensions, and in relation to the exercise being performed. Our findings suggest that, although certain differences can be observed between the four dimensions, the most influential factor on ensemble interdependence is the musical task, shaped by the underlying score.The work presented on this document has been partially supported by the EU-FP7 FET SIEMPRE project and an AGAUR research grant from Generalitat de Catalunya

Computational analysis of solo versus ensemble performance in string quartets: intonation and dynamics

Comunicació presentada a la conferència conjunta que inclou la 12th International Conference on Music Perception and Cognition (ICMPC) i la 8th Triennial Conference of the European Society, celebrada a Tessalònica (Grècia) els dies 23 a 28 de juliol de 2012.Musical ensembles, such as a string quartet, are a clear case of music performance where a joint interpretation of the score as well as joint action during the performance is required by the musicians. Of the several explicit and implicit ways through which the musicians cooperate, we focus on the acoustic result of the performance – in this case in terms of dynamics and intonation - and attempt to detect evidence of interdependence among the musicians by performing a computational analysis. We have recorded a set of string quartet exercises whose challenge lies in achieving ensemble cohesion rather than correctly performing one’s individual task successfully, which serve as a ‘ground truth’ dataset; these exercises were recorded by a professional string quartet in two experimental conditions: solo, where each musician performs their part alone without having access to the full quartet score, and ensemble, where the musicians perform the exercise together following a short rehearsal period. Through an automatic analysis and post-processing of audio and motion capture data, we extract a set of low-level features, on which we apply several numerical methods of interdependence (such as Pearson correlation, Mutual Information, Granger causality, and Nonlinear coupling) in order to measure the interdependence -or lack thereofamong the musicians during the performance. Results show that, although dependent on the underlying musical score, this methodology can be used in order to automatically analyze the performance of a musical ensemble.The work presented on this document has been partially supported by the EU-FP7 FET SIEMPRE project and an AGAUR research grant from Generalitat de Catalunya

Computational analysis of solo versus ensemble performance in string quartets: intonation and dynamics

Comunicació presentada a la conferència conjunta que inclou la 12th International Conference on Music Perception and Cognition (ICMPC) i la 8th Triennial Conference of the European Society, celebrada a Tessalònica (Grècia) els dies 23 a 28 de juliol de 2012.Musical ensembles, such as a string quartet, are a clear case of music performance where a joint interpretation of the score as well as joint action during the performance is required by the musicians. Of the several explicit and implicit ways through which the musicians cooperate, we focus on the acoustic result of the performance – in this case in terms of dynamics and intonation - and attempt to detect evidence of interdependence among the musicians by performing a computational analysis. We have recorded a set of string quartet exercises whose challenge lies in achieving ensemble cohesion rather than correctly performing one’s individual task successfully, which serve as a ‘ground truth’ dataset; these exercises were recorded by a professional string quartet in two experimental conditions: solo, where each musician performs their part alone without having access to the full quartet score, and ensemble, where the musicians perform the exercise together following a short rehearsal period. Through an automatic analysis and post-processing of audio and motion capture data, we extract a set of low-level features, on which we apply several numerical methods of interdependence (such as Pearson correlation, Mutual Information, Granger causality, and Nonlinear coupling) in order to measure the interdependence -or lack thereofamong the musicians during the performance. Results show that, although dependent on the underlying musical score, this methodology can be used in order to automatically analyze the performance of a musical ensemble.The work presented on this document has been partially supported by the EU-FP7 FET SIEMPRE project and an AGAUR research grant from Generalitat de Catalunya