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

Perspectives and approaches to determine measures of similarity for musical performances using data analysis algorithms

La caracterización automática de obras musicales, e intérpretes de las mismas, es objeto de investigación en la actualidad. Debido principalmente a la importancia del tópico, pero también al auge tecnológico y la disposición de herramientas computacionales capaces de detectar voz y sonido. El reconocimiento automático de una composición, así como su intérprete y características relevantes desde el punto de vista musical, ha mantenido a una comunidad de investigadores en la búsqueda de medidas que permitan hacer comparaciones e inferir con precisión sobre las características de la composición y el intérprete; sin embargo, esta medida aún está por descubrirse, aunque se han generado diversas técnicas estadístico-computacionales que merecen ser evaluadas y quizás combinadas para fortalecer cualquier investigación en este tópico. Este trabajo, producto de una basta revisión bibliográfica, recoge las principales técnicas y herramientas que han sido utilizadas y propuestas por investigadores en las últimas dos décadas. El documento será de ayuda a los investigadores que decidan emprender estudios, evaluaciones e implementaciones de estas herramientas, así como también aquellos que deseen trabajar en el reconocimiento automático de obras musicales, sus características e intérpretes, o recuperación de información musical.The automatic characterization of a musical composition, and its interpretation, is a current line of research, due to its importance and the technological resources available and computational tools capable for detecting voice and sound. The recognition of an interpreter when listening a composition is simple for a human, but not as simple for machines, thus, this topic has kept a community of researchers in search of measures to compare and accurately recognize the composition characteristics and the interpreter. However, still a general measure has yet to be discovered, although various statistical-computational techniques have been generated and deserve to be evaluated and perhaps combined to strengthen any research on this topic. This work is the product of a comprehensive literature review that collects the main techniques and tools that have been used and proposed by researchers over the last two decades. The document will be of help to researchers who decide to undertake studies, evaluations and implementations of these tools, as well as those who wish to work on automatic recognition of interpreters and characteristics of musical compositions, or music information retrieval

Music composition based on Artificial Neural Networks

In the recent years, research on Artificial Intelligence has ushered in a new phase of technology evolution. Autonomous systems such as voice assistants or self-driving cars are a present reality as first commercial systems have been already launched to the market. New applications emerge each year as huge amounts of generated data and computational capabilities make the development of accurate and expert systems plausible. This evolution is optimizing processes of many core fields such as agriculture, telecommunications or medicine. A quite technological field such as music is also beginning to notice changes, as recommendation engines, synthesizers and music generation are attractive fields of research with some preliminary results. With this project, we intend to contribute to ease the process of music creation making it more accessible to people. The subject of this project is the design, development and experimentation of an AI engine to generate music. A simple, but pleasant to hear artificially generated melody could serve as a base for people to compose more complex pieces of music. At the same time, the project sheds some light to the nuts and bolts of novel techniques for music composition, as the Long Short Term Memory network selected. The system processes MIDI files and extracts relevant information for training the network. The extracted data has been selected by analyzing the main aspects used in the field of Music Information Retrieval. An online listening test taken by subjects of different musical backgrounds is designed to measure the quality of the artificial composer. The final results prove that pleasant to hear melodies have been composed.Ingeniería de Sistemas Audiovisuale

Improvisatory music and painting interface

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2004.Includes bibliographical references (p. 101-104).(cont.) theoretical section is accompanied by descriptions of historic and contemporary works that have influenced IMPI.Shaping collective free improvisations in order to obtain solid and succinct works with surprising and synchronized events is not an easy task. This thesis is a proposal towards that goal. It presents the theoretical, philosophical and technical framework of the Improvisatory Music and Painting Interface (IMPI) system: a new computer program for the creation of audiovisual improvisations performed in real time by ensembles of acoustic musicians. The coordination of these improvisations is obtained using a graphical language. This language is employed by one "conductor" in order to generate musical scores and abstract visual animations in real time. Doodling on a digital tablet following the syntax of the language allows both the creation of musical material with different levels of improvisatory participation from the ensemble and also the manipulation of the projected graphics in coordination with the music. The generated musical information is displayed in several formats on multiple computer screens that members of the ensemble play from. The digital graphics are also projected on a screen to be seen by an audience. This system is intended for a non-tonal, non-rhythmic, and texture-oriented musical style, which means that strong emphasis is put on the control of timbral qualities and continuum transitions. One of the main goals of the system is the translation of planned compositional elements (such as precise structure and synchronization between instruments) into the improvisatory domain. The graphics that IMPI generates are organic, fluid, vivid, dynamic, and unified with the music. The concept of controlled improvisation as well as the paradigm of the relationships between acoustic and visual material are both analyzed from an aesthetic point of view. TheHugo Solís García.S.M

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

Music conducting pedagogy and technology : a document analysis on best practices

This document analysis was designed to investigate pedagogical practices of music conducting teachers in conjunction with research of technologists on the use of various technologies as teaching tools. I sought to discern how conducting teachers and pedagogues are applying recent technological advancements into their teaching strategies. I also sought to understand what paths research is taking about the use of software, hardware, and computer systems applied to the teaching of music conducting technique. This dissertation was guided by four main research questions: (1) How has technology been used to aid in the teaching of conducting? (2) What is the role of technology in the context of conducting pedagogy? (3) Given that conducting is a performative act, how can it be developed through technological means? (4) What technological possibilities exist in the teaching of music conducting technique? Data were collected through music conducting syllabi, conducting textbooks, and research articles. Documents were selected through purposive sampling procedures. Analysis of documents through the constant comparative approach identified emerging themes and differences across the three types of documents. Based on a synthesis of information, I discussed implications for conducting pedagogy and made suggestions for conducting educators.Includes bibliographical references