0
Your cart

Your cart is empty

Browse All Departments
  • All Departments
Price
  • R1,000 - R2,500 (1)
  • R2,500 - R5,000 (1)
  • -
Status
Brand

Showing 1 - 2 of 2 matches in All Departments

Machine Learning and Music Generation (Hardcover): Jose M Inesta, Rafael Ramirez Melendez, Darrell C. Conklin, Thomas M. Fiore Machine Learning and Music Generation (Hardcover)
Jose M Inesta, Rafael Ramirez Melendez, Darrell C. Conklin, Thomas M. Fiore
R4,614 Discovery Miles 46 140 Ships in 12 - 19 working days

Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.

Machine Learning and Music Generation (Paperback): Jose M Inesta, Rafael Ramirez Melendez, Darrell C. Conklin, Thomas M. Fiore Machine Learning and Music Generation (Paperback)
Jose M Inesta, Rafael Ramirez Melendez, Darrell C. Conklin, Thomas M. Fiore
R1,419 Discovery Miles 14 190 Ships in 12 - 19 working days

Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.

Free Delivery
Pinterest Twitter Facebook Google+
You may like...
Islam, State and Society in Indonesia…
Yanwar Pribadi Hardcover R4,471 Discovery Miles 44 710
Profiles of Patriots - A Biographical…
Moira Ann Jacobs Hardcover R801 Discovery Miles 8 010
The Goffman Reader
C Lemert Hardcover R4,730 Discovery Miles 47 300
IQ A4 80gsm Pastel Green Paper (1 Ream)
R214 Discovery Miles 2 140
The Lives of the Most Eminent British…
Allan Cunningham Paperback R526 Discovery Miles 5 260
Governing Territorial Development in the…
Erblin Berisha, Giancarlo Cotella, … Hardcover R4,944 Discovery Miles 49 440
Picturing Greensboro - Four Decades of…
Otis L. Hairston Paperback R500 R469 Discovery Miles 4 690
From Lying to Perjury - Linguistic and…
Laurence R. Horn Hardcover R3,876 Discovery Miles 38 760
This Is How It Is - True Stories From…
The Life Righting Collective Paperback R265 R245 Discovery Miles 2 450
Cherokee Narratives - A Linguistic Study
Durbin Feeling, William Pulte, … Hardcover R1,005 Discovery Miles 10 050

 

Partners