Dynamic Musical Orchestration Using Genetic Algorithms and a Spectro-Temporal Description of Musical Instruments

Esling, Philippe; Carpentier, Grégoire; Agón, Carlos

doi:10.1007/978-3-642-12242-2_38

Cited by 14 publications

(11 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It is everything but a straightforward problem, as timbre is already a multidimensional object, and considering time is not like adding a single new dimension. Recent and promising research (Esling, Carpentier, and Agon 2010) has begun exploring that direction, by means of advanced temporal models implying a significant increase in the number of parameters. As far as we are concerned, we still believe that it is worth trying to go as far as possible with a small set of parameters, ensuring maximal user control and perceptual significance.…”

Section: Discussion and Future Perspectivesmentioning

confidence: 99%

Automatic Orchestration in Practice

Carpentier

Daubresse

Vitoria³

et al. 2012

Computer Music Journal

Self Cite

View full text Add to dashboard Cite

We report here on the recent use of the Orchidée software by three different young composers in various compositional and instrumental contexts. Orchidée is a computer-aided orchestration environment designed to aid musicians exploring the space of instrument timbre mixtures and finding timbre combinations that fit a set of user-specified perceptual requirements. The first beta version of the software was released by the Institut de Recherche et Coordination Acoustique/Musique's (IRCAM's) Music Representations Group in 2009, after four years of intensive research, and it can already handle a small range of real-life situations, typically timbre imitation or orchestral synthesis, under instrumental constraints. Detailed examples, including score and audio excerpts, are provided. Computer Music Journal

show abstract

Section: Discussion and Future Perspectivesmentioning

confidence: 99%

Automatic Orchestration in Practice

Carpentier

Daubresse

Vitoria³

et al. 2012

Computer Music Journal

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, major works have refined our understanding of the perceptual and cognitive mechanisms specifically involved when listening to instrumental mixtures [15,22,25]. Orchids, an advanced tool for assisting composers in the search of a particular sonic goal has been developed [8]. It relies on the multi-objective optimization of several spectro-temporal features such as those described in [20].…”

Section: A Scientific Investigation Of Orchestrationmentioning

confidence: 99%

“…Orchestration is the subtle art of writing musical pieces for the orchestra by combining the properties of various instruments in order to achieve a particular musical idea [11,23]. Among the variety of writing techniques for orchestra, we define as projective orchestration [8] the technique which consists in first writing a piano score and then orchestrating it (akin to a projection operation, as depicted in Figure 1). This technique has been used by classic composers for centuries.…”

Section: Introductionmentioning

confidence: 99%

A database linking piano and orchestral MIDI scores with application to automatic projective orchestration

Crestel,

Esling,

Heng

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

This article introduces the Projective Orchestral Database (POD), a collection of MIDI scores composed of pairs linking piano scores to their corresponding orchestrations. To the best of our knowledge, this is the first database of its kind, which performs piano or orchestral prediction, but more importantly which tries to learn the correlations between piano and orchestral scores. Hence, we also introduce the projective orchestration task, which consists in learning how to perform the automatic orchestration of a piano score. We show how this task can be addressed using learning methods and also provide methodological guidelines in order to properly use this database.

show abstract

“…Un des premiers problèmes traités est l'optimisation du codage et de l'indexation des ces séries dans les bases de données pour permettre un traitement des requêtes efficace. Un deuxième défi, en lien avec les problématiques du §2.3, est ensuite de détecter, décrire et de reproduire correctement les spectromorphologies avec leur dynamique temporelle, ce qui a des implications non seulement sur la sélection des échantillons ou modèles instrumentaux mais aussi sur leur ordonnancement temporel (Esling et al, 2010).…”

Section: Synthèse Et Perspectivesunclassified

Sample Orchestrator : gestion par le contenu d’échantillons sonores

Vinet¹,

Assayag²,

Burred

et al. 2011

Traitement du signal

View full text Add to dashboard Cite

RÉSUMÉ. Nous présentons les principaux travaux menés dans le projet Sample Orchestrator, destiné au développement de fonctions innovantes de manipulation d'échantillons sonores. Celles-ci se fondent sur des études consacrées à la description des sons, c'est-à-dire à la formalisation de structures de données pertinentes pour caractériser le contenu et l'organisation des sons. Ces travaux ont été appliqués à l'indexation automatique des sons, ainsi qu'à la réalisation d'applications inédites pour la création musicale -synthèse sonore interactive par corpus et aide informatisée à l'orchestration. Le projet a aussi comporté un important volet consacré au traitement de haute qualité des sons, à travers plusieurs RÉSUMÉ ÉTENDU EN ANGLAISThe Sample Orchestrator R&D project was aimed at the development of innovative functions for the content-based manipulation of sound samples. Its main objectives and advances are summarized hereinafter. Sound description and automatic indexingThis objective concerns the development of new heuristics for managing sample databases. The sound description issue involves a top-down process for elaborating representations of the sound world relevant to the human cognition. Recent studies define three levels for sound similarity: semantic, causal and acoustic. Causal relates to the sound production in terms of sources and actions. For each homogeneous sound set, a specific timbre space, with dimensions directly correlated to acoustical attributes, can be obtained. A first study consisted in performing a meta-analysis of timbre spaces resulting from several studies related to different sound corpora. A second study was dedicated to an experience of categorization of a given corpus of environmental sounds targeted to the materials of the sources. The results show a good correlation between the experimental data and the actual categories. Three labeled corpora were elaborated from these experiences: Materials, Reduced materials and Onomatopoeia.The second stage, automatic indexing, aimed at building a signal model of the classes in order to perform the automatic classification of new sounds from the analysis of their signals. First, an extensive set of audio descriptors, combining several models (spectral, harmonic, perceptual) was elaborated and implemented as the IrcamDescriptor library. For the learning phase of classification, an algorithm provides a selection of descriptors for a given set of classes. After applying an LDA, various supervised classification methods were evaluated. The best results were obtained with an SVM, with accuracies and f-measures greater than 70% for the 3 formerly produced corpora.A last study concerned the categorization of sound morphologies. 6 classes emerged from an experience on intensity profiles and very good results were obtained for the automatic classification with a binary decision tree operating on selected descriptors. High-quality sound processingThis objective consisted in extending the phase vocoder model for high-quality sound processing. The model...

show abstract

Dynamic Musical Orchestration Using Genetic Algorithms and a Spectro-Temporal Description of Musical Instruments

Cited by 14 publications

References 9 publications

Automatic Orchestration in Practice

Automatic Orchestration in Practice

A database linking piano and orchestral MIDI scores with application to automatic projective orchestration

Sample Orchestrator : gestion par le contenu d’échantillons sonores

Contact Info

Product

Resources

About