Peran Fingering Pada Teknik Pizzicato Dan Harmonics Dalam Reinterpretasi Karya Maurice Ravel

Tujuan dari penelitian ini adalah mengetahui peran fingering pada teknik pizzicato dan harmonics dalam upaya reinterpretasi terhadap repertoar Tzigane karya Maurice Ravel. Sering kita jumpai bahwa solois menerapkan penjarian yang berbeda dari penjarian yang sudah ditentukan dalam partitur. Tidak hanya itu, perbedaan juga terjadi antara solois yang satu dan yang lainnya meskipun memainkan karya yang sama. Penelitian ini menggunakan teori yang meliputi fingering, pizzicato, harmonic dan interpretasi yang nantinya akan membantu dalam proses realisasi pada dinamika, warna suara dan artikulasi sebagai bentuk dari reinterpretasi seorang solois.  Metode Penelitian yang digunakan adalah metode kualitatif dengan pendekatan studi kasus. Kasus yang digunakan adalah teknik pizzicato dan harmonics pada repertoar Tzigane karya Maurice Ravel. Hasil penelitian menunjukkan bahwa fingering pada teknik pizzicato mempengaruhi keberhasilan solois dalam merealisasikan reinterpretasi melalui teknik. Sedangkan fingering pada teknik harmonics dapat mendukung solois dalam merubah atau menguatkan kesan musikal tertentu berdasarkan rancangan reinterpretasi (blueprint).Kata kunci : fingering, pizzicato, harmonics, reinterpretasi, Maurice Ravel. ABSTRACTThe Role Of Fingering In Pizzicato And Harmonics Techniques In Reinterpretation Of Maurice Ravel's WorksThe purpose of this study was determine the role of fingering in the pizzicato technique and harmonics in an effort to reinterpret Maurice Ravel's Tzigane repertoire. We often find that the soloist applies fingering that is different from the fingering that has been determined in the scores. Not only that, differences also occur between one soloist and another even though they play the same work. This Study used the theory that includes fingering, pizzicato, harmonics and interpretation, which will help the process of realizing dynamics, timbre and articulation as a form of reinterpretation by a soloist. The research method used is a qualitative method with a case study approach. The case used is the pizzicato technique and harmonics in Maurice Ravel's Tzigane repertoire. The results of the study show that fingering in the pizzicato technique influences the success of the soloist in realizing reinterpretation through technique. Meanwhile, fingering in harmonics techniques can support soloists in changing or strengthening certain musical impressions based on reinterpretation designs (blueprints).Keywords: fingering, pizzicato, harmonics, reinterpretation, Maurice Ravel

Machine Annotation of Traditional Irish Dance Music

The work presented in this thesis is validated in experiments using 130 realworld field recordings of traditional music from sessions, classes, concerts and commercial recordings. Test audio includes solo and ensemble playing on a variety of instruments recorded in real-world settings such as noisy public sessions. Results are reported using standard measures from the field of information retrieval (IR) including accuracy, error, precision and recall and the system is compared to alternative approaches for CBMIR common in the literature

Probabilistic characterization and synthesis of complex driven systems

Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000.Includes bibliographical references (leaves 194-204).Real-world systems that have characteristic input-output patterns but don't provide access to their internal states are as numerous as they are difficult to model. This dissertation introduces a modeling language for estimating and emulating the behavior of such systems given time series data. As a benchmark test, a digital violin is designed from observing the performance of an instrument. Cluster-weighted modeling (CWM), a mixture density estimator around local models, is presented as a framework for function approximation and for the prediction and characterization of nonlinear time series. The general model architecture and estimation algorithm are presented and extended to system characterization tools such as estimator uncertainty, predictor uncertainty and the correlation dimension of the data set. Furthermore a real-time implementation, a Hidden-Markov architecture, and function approximation under constraints are derived within the framework. CWM is then applied in the context of different problems and data sets, leading to architectures such as cluster-weighted classification, cluster-weighted estimation, and cluster-weighted sampling. Each application relies on a specific data representation, specific pre and post-processing algorithms, and a specific hybrid of CWM. The third part of this thesis introduces data-driven modeling of acoustic instruments, a novel technique for audio synthesis. CWM is applied along with new sensor technology and various audio representations to estimate models of violin-family instruments. The approach is demonstrated by synthesizing highly accurate violin sounds given off-line input data as well as cello sounds given real-time input data from a cello player.by Bernd Schoner.Ph.D

Computational Models of Expressive Music Performance: A Comprehensive and Critical Review

Expressive performance is an indispensable part of music making. When playing a piece, expert performers shape various parameters (tempo, timing, dynamics, intonation, articulation, etc.) in ways that are not prescribed by the notated score, in this way producing an expressive rendition that brings out dramatic, affective, and emotional qualities that may engage and affect the listeners. Given the central importance of this skill for many kinds of music, expressive performance has become an important research topic for disciplines like musicology, music psychology, etc. This paper focuses on a specific thread of research: work on computational music performance models. Computational models are attempts at codifying hypotheses about expressive performance in terms of mathematical formulas or computer programs, so that they can be evaluated in systematic and quantitative ways. Such models can serve at least two purposes: they permit us to systematically study certain hypotheses regarding performance; and they can be used as tools to generate automated or semi-automated performances, in artistic or educational contexts. The present article presents an up-to-date overview of the state of the art in this domain. We explore recent trends in the field, such as a strong focus on data-driven (machine learning) approaches; a growing interest in interactive expressive systems, such as conductor simulators and automatic accompaniment systems; and an increased interest in exploring cognitively plausible features and models. We provide an in-depth discussion of several important design choices in such computer models, and discuss a crucial (and still largely unsolved) problem that is hindering systematic progress: the question of how to evaluate such models in scientifically and musically meaningful ways. From all this, we finally derive some research directions that should be pursued with priority, in order to advance the field and our understanding of expressive music performance

Proceedings of the 7th Sound and Music Computing Conference

Proceedings of the SMC2010 - 7th Sound and Music Computing Conference, July 21st - July 24th 2010

Sequential decision making in artificial musical intelligence

Over the past 60 years, artificial intelligence has grown from a largely academic field of research to a ubiquitous array of tools and approaches used in everyday technology. Despite its many recent successes and growing prevalence, certain meaningful facets of computational intelligence have not been as thoroughly explored. Such additional facets cover a wide array of complex mental tasks which humans carry out easily, yet are difficult for computers to mimic. A prime example of a domain in which human intelligence thrives, but machine understanding is still fairly limited, is music. Over the last decade, many researchers have applied computational tools to carry out tasks such as genre identification, music summarization, music database querying, and melodic segmentation. While these are all useful algorithmic solutions, we are still a long way from constructing complete music agents, able to mimic (at least partially) the complexity with which humans approach music. One key aspect which hasn't been sufficiently studied is that of sequential decision making in musical intelligence. This thesis strives to answer the following question: Can a sequential decision making perspective guide us in the creation of better music agents, and social agents in general? And if so, how? More specifically, this thesis focuses on two aspects of musical intelligence: music recommendation and human-agent (and more generally agent-agent) interaction in the context of music. The key contributions of this thesis are the design of better music playlist recommendation algorithms; the design of algorithms for tracking user preferences over time; new approaches for modeling people's behavior in situations that involve music; and the design of agents capable of meaningful interaction with humans and other agents in a setting where music plays a roll (either directly or indirectly). Though motivated primarily by music-related tasks, and focusing largely on people's musical preferences, this thesis also establishes that insights from music-specific case studies can also be applicable in other concrete social domains, such as different types of content recommendation. Showing the generality of insights from musical data in other contexts serves as evidence for the utility of music domains as testbeds for the development of general artificial intelligence techniques. Ultimately, this thesis demonstrates the overall usefulness of taking a sequential decision making approach in settings previously unexplored from this perspectiveComputer Science

Study on Perception-Action Scheme for Human-Robot Musical Interaction in Wind Instrumental Play

制度:新 ; 報告番号:甲3337号 ; 学位の種類:博士(工学) ; 授与年月日:2011/2/25 ; 早大学位記番号:新564