Download Free Machine Music Book in PDF and EPUB Free Download. You can read online Machine Music and write the review.

Machine Models of Music brings together representative models and current research to illustrate the rich impact that artificial intelligence has had on the understanding and composition of traditional music and to demonstrate the ways in which music can push the boundaries of traditional Al research. Machine Models of Music brings together representative models ranging from Mozart's "Musical Dice Game" to a classic article by Marvin Minsky and current research to illustrate the rich impact that artificial intelligence has had on the understanding and composition of traditional music and to demonstrate the ways in which music can push the boundaries of traditional Al research.Major sections of the book take up pioneering research in generate-and-test composition (Lejaren Hiller, Barry Brooks, Jr., Stanley Gill); composition parsing (Allen Forte, Herbert Simon, Terry Winograd); heuristic composition (John Rothgeb, James Moorer, Steven Smoliar); generative grammars (Otto Laske, Gary Rader, Johan Sundberg, Fred Lerdahl); alternative theories (Marvin Minsky, James Meehan); composition tools (Charles Ames, Kemal Ebcioglu, David Cope, C. Fry); and new directions (David Levitt, Christopher Longuet-Higgins, Jamshed Bharucha, Stephan Schwanauer).Stephan Schwanauer is President of Mediasoft Corporation. David Levitt is the founder of HIP Software and head of audio products at VPL Research.
In The Music Machine, Curtis Roads brings together 53 classic articles published in Computer Music Journal between 1980 and 1985.
Sound and music is a product of technology. Whether we are enjoying a concert, working in a sound studio or listening with headphones on, technical equipment lays the foundation of our musical experience. In Machine Music. A Media Archaeological Excavation postdoc, composer and PhD Morten Riis tunes into normally undetected layers of music. Musical machines - be it ancient or modern instruments, computers, loudspeakers or amplifiers - are not just silent mediators of sounds. They all have their own unique voices. We simply have to learn to listen to them.
Whether you want to start a record label, self-release your own music, or are just an avid music lover, this book will give you information about the business of music. The Label Machine: How to Start, Run and Grow Your Own Independent Music Label is the first book to give music artists practical step-by-step comprehensive instructions for setting up and running an independent music label to successfully distribute and market their music. You will learn all about the music industry business and how to navigate the tricky dos and don'ts. You will finally understand and take control of your music copyright and get to grips with the legalities involved. You will build your music business effortlessly, learning how to professionally market your music and artists - allowing you to reach thousands of fans. And essentially, you will learn how to create multiple label revenue streams to create an established record label. It features a detailed breakdown of how every part of the industry works together, including copyright in the UK and US, record label set-up, record releases, and royalty collection. It also provides in-depth guides on marketing, covering; traditional PR, Facebook and Instagram advertising, Spotify playlisting, and fan growth. Includes templates for record label and management contracts, marketing and promotion schedules, press releases, and fan email automation.
1/2 page flaps. Based on BBC TV characters. 2-5 yrs.
"An utterly satisfying examination of the business of popular music." —Nathaniel Rich, The Atlantic There’s a reason today’s ubiquitous pop hits are so hard to ignore—they’re designed that way. The Song Machine goes behind the scenes to offer an insider’s look at the global hit factories manufacturing the songs that have everyone hooked. Full of vivid, unexpected characters—alongside industry heavy-hitters like Katy Perry, Rihanna, Max Martin, and Ester Dean—this fascinating journey into the strange world of pop music reveals how a new approach to crafting smash hits is transforming marketing, technology, and even listeners’ brains. You’ll never think about music the same way again. A Wall Street Journal Best Business Book
Having a moon for a head at high school is a pretty tricky situation. But when the school talent contest is announced, Joey Moonhead spots an opportunity to impress his classmates with a music machine. An imaginative and visually poetic take on the stock American high school drama, this is one graphic novel that's out of this world!
A pulsating graphic novel on the epic history of electronic music, from the heyday of disco in the 1970s to the rave culture of the 1990s and beyond. With a foreword from house music legends Daft Punk, The Song of the Machine is a celebration of a musical wave that swept across the world over decades, demographics, and dance styles. Originally published in 2000 in France, and updated through today for this first English edition, the electrifying narrative introduces readers to the harbingers of the genre, such as David Mancuso, Larry Levan, and Frankie Knuckles (known as the "Godfather of House Music"); the prototypes of modern-day nightclubs and dance venues, like The Loft and Studio 54 in New York City, the Palace in Paris, and the Hacienda in Manchester, England, and of course, the technology and machines that first produced and synthesized the records that galvanized a movement. Told through exciting illustrations that evolve with the era they describe, and complete with specially curated playlists for each and every decade, The Song of the Machine recounts the influences and inspirations, the people and epic parties that created and defined this revolutionary music.
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.