Generating a Complete Multipart Musical Composition from a Single Monophonic Melody with Functional Scaffolding

نویسندگان

  • Amy K. Hoover
  • Paul A. Szerlip
  • Marie E. Norton
  • Trevor A. Brindle
  • Zachary Merritt
  • Kenneth O. Stanley
چکیده

This paper advances the state of the art for a computer-assisted approach to music generation called functional scaffolding for musical composition (FSMC), whose representation facilitates creative combination, exploration, and transformation of musical concepts. Music in FSMC is represented as a functional relationship between an existing human composition, or scaffold, and a generated accompaniment. This relationship is encoded by a type of artificial neural network called a compositional pattern producing network (CPPN). A human user without any musical expertise can then explore how accompaniment should relate to the scaffold through an interactive evolutionary process akin to animal breeding. While the power of such a functional representation has previously been shown to constrain the search to plausible accompaniments, this study goes further by showing that the user can tailor complete multipart arrangements from only a single original monophonic track provided by the user, thus enabling creativity without the need for musical expertise.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Demo: A Computer-Assisted Approach to Composing with MaestroGenesis

This demonstration presents MaestroGenesis, a program that helps users create complete polyphonic musical pieces from as little as a simple, human composed monophonic melody. MaestroGenesis creates music by exploiting two key ideas behind the functional scaffolding for musical composition (FSMC) approach: (1) that music a function of time and (2) that functional transformations of initial human...

متن کامل

Generating Musical Accompaniment through Functional Scaffolding

A popular approach to music generation in recent years is to extract rules and statistical relationships by analyzing a large corpus of musical data. The aim of this paper is to present an alternative to such data-intensive techniques. The main idea, called functional scaffolding for musical composition (FSMC), exploits a simple yet powerful property of multipart compositions: The pattern of no...

متن کامل

Functional Scaffolding for Composing Additional Musical Voices

Many tools for computer-assisted composition contain built-in music-theoretical assumptions that may constrain the output to particular styles. In contrast, this article presents a new musical representation that contains almost no built-in knowledge, but that allows even musically untrained users to generate polyphonic textures that are derived from the users’ own initial compositions. This re...

متن کامل

Musical style classification from symbolic data: A two-styles case study

In this paper the classification of monophonic melodies from two different musical styles (Jazz and classical) is studied using different classification methods: Bayesian classifier, a k-NN classifier, and selforganising maps (SOM). From MIDI files, the monophonic melody track is extracted and cut into fragments of equal length. From these sequences, A number of melodic, harmonic, and rhythmic ...

متن کامل

MaestroGenesis: Computer-Assisted Musical Accompaniment Generation

This demonstration presents an implementation of a computer-assisted approach to music generation called functional sca↵olding for musical composition (FSMC) whose representation facilitates creative combination, exploration, and transformation of musical ideas and spaces. The approach is demonstrated through a program called MaestroGenesis with a convenient GUI that makes it accessible to even...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012