pDaniM: A case study on interactive processes for expressive music generation in the computer animataion production pipeline

This paper presents an experimental application that shows how an interactive process can save time and production resources in the process pipeline of music scoring for a 3D animation movie. This investigation uses as basis several rules (about 30) that performers use to add certain expressive emotions to a score, covering different aspects of music performance. Basically, applying the rules produces a rearrange in time and velocity parameters such as “microtiming”, articulation, tempo and sound level. The resulting application should take as input a basic music score (MIDI) quantized linearly, and imprint expressiveness and emotion to this music in sync with the expressiveness cues from the timeline exported from the animation project. Acoustic cues are driven by facial and gesture expression from the characters

The influence of body movements on children's perception of music with an ambiguous expressive character

The theory of embodied music cognition states that the perception and cognition of music is firmly, although not exclusively, linked to action patterns associated with that music. In this regard, the focus lies mostly on how music promotes certain action tendencies (i.e., dance, entrainment, etc.). Only recently, studies have started to devote attention to the reciprocal effects that people’s body movements may exert on how people perceive certain aspects of music and sound (e.g., pitch, meter, musical preference, etc.). The present study positions itself in this line of research. The central research question is whether expressive body movements, which are systematically paired with music, can modulate children’s perception of musical expressiveness. We present a behavioral experiment in which different groups of children (7–8 years, N = 46) either repetitively performed a happy or a sad choreography in response to expressively ambiguous music or merely listened to that music. The results of our study show indeed that children’s perception of musical expressiveness is modulated in accordance with the expressive character of the dance choreography performed to the music. This finding supports theories that claim a strong connection between action and perception, although further research is needed to uncover the details of this connection

Analyzing Visual Mappings of Traditional and Alternative Music Notation

In this paper, we postulate that combining the domains of information visualization and music studies paves the ground for a more structured analysis of the design space of music notation, enabling the creation of alternative music notations that are tailored to different users and their tasks. Hence, we discuss the instantiation of a design and visualization pipeline for music notation that follows a structured approach, based on the fundamental concepts of information and data visualization. This enables practitioners and researchers of digital humanities and information visualization, alike, to conceptualize, create, and analyze novel music notation methods. Based on the analysis of relevant stakeholders and their usage of music notation as a mean of communication, we identify a set of relevant features typically encoded in different annotations and encodings, as used by interpreters, performers, and readers of music. We analyze the visual mappings of musical dimensions for varying notation methods to highlight gaps and frequent usages of encodings, visual channels, and Gestalt laws. This detailed analysis leads us to the conclusion that such an under-researched area in information visualization holds the potential for fundamental research. This paper discusses possible research opportunities, open challenges, and arguments that can be pursued in the process of analyzing, improving, or rethinking existing music notation systems and techniques.Comment: 5 pages including references, 3rd Workshop on Visualization for the Digital Humanities, Vis4DH, IEEE Vis 201

Timbre from Sound Synthesis and High-level Control Perspectives

International audienceExploring the many surprising facets of timbre through sound manipulations has been a common practice among composers and instrument makers of all times. The digital era radically changed the approach to sounds thanks to the unlimited possibilities offered by computers that made it possible to investigate sounds without physical constraints. In this chapter we describe investigations on timbre based on the analysis by synthesis approach that consists in using digital synthesis algorithms to reproduce sounds and further modify the parameters of the algorithms to investigate their perceptual relevance. In the first part of the chapter timbre is investigated in a musical context. An examination of the sound quality of different wood species for xylophone making is first presented. Then the influence of instrumental control on timbre is described in the case of clarinet and cello performances. In the second part of the chapter, we mainly focus on the identification of sound morphologies, so called invariant sound structures responsible for the evocations induced by environmental sounds by relating basic signal descriptors and timbre descriptors to evocations in the case of car door noises, motor noises, solid objects, and their interactions

Identification of expressive descriptors for style extraction in music analysis using linear and nonlinear models

La formalización de las interpretaciones expresivas aún se considera relevante debido a la complejidad de la música. La interpretación expresiva forma un aspecto importante de la música, teniendo en cuenta diferentes convenciones como géneros o estilos que una interpretación puede desarrollar con el tiempo. Modelar la relación entre las expresiones musicales y los aspectos estructurales de la información acústica requiere una base probabilística y estadística mínima para la robustez, validación y reproducibilidad de aplicaciones computacionales. Por lo tanto, es necesaria una relación cohesiva y una justificación sobre los resultados. Esta tesis se sustenta en la teoría y aplicaciones de modelos discriminativos y generativos en el marco del aprendizaje de maquina y la relación de procedimientos sistemáticos con los conceptos de la musicología utilizando técnicas de procesamiento de señales y minería de datos. Los resultados se validaron mediante pruebas estadísticas y una experimentación no paramétrica con la implementación de un conjunto de métricas para medir aspectos acústicos y temporales de archivos de audio para entrenar un modelo discriminativo y mejorar el proceso de síntesis de un modelo neuronal profundo. Adicionalmente, el modelo implementado presenta la oportunidad para la aplicación de procedimientos sistemáticos, automatización de transcripciones usando notación musical, entrenamiento de habilidades auditivas para estudiantes de música y mejorar la implementación de redes neuronales profundas usando CPU en lugar de GPU debido a las ventajas de las redes convolucionales para el procesamiento de archivos de audio como vectores o matriz con una secuencia de notas.MaestríaMagister en Ingeniería Electrónic