AI for Songwriters: How Audio Transformer Models Generate Songs | Artificial Intelligence | Berklee

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In this video from the Berklee Online AI for Songwriters course, instructor Ben Camp explains how audio transformer models generate songs. If you zoom in on a sound wave, you’ll see a series of dots. A regular waveform consists of approximately 44.1 dots per second, which means 44,100 samples per second. Camp takes a sample of a waveform and breaks it down into four separate tokens, each one containing 10 samples (10 dots) where the end dots of one token connect smoothly to the first dot of the next one. Audio models are used to figure out which token comes next, where artificial intelligence is used to match tokens adequately so it can play an entire song matching a series of several tokens.

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ABOUT THE AUTHOR:
Ben Camp teaches songwriting at Berklee College of Music. Their songs have appeared in film and TV on networks like MTV, CBS, NBC, Fox, and more. They have written singles for Brice Fox, Tiesto, Victoria Justice, Sam Feldt, and others. Ben’s mission as an educator is simple: Help you write the songs that only you can write.

About Berklee Online:
Founded in 2002, Berklee Online is the premier innovator and largest provider of worldwide music education, offering the renowned curriculum of Berklee College of Music at a fraction of the cost through award-winning programming and instruction. Contact an Academic Advisor today:
1-866-BERKLEE (US)
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AI for Songwriters | Songwriting | Artificial Intelligence | Audio | Technology | Ben Camp | Berklee College of Music | Berklee Online | songwriter | Brice Fox | Tiesto | Victoria Justice | Sam Feldt | Token | Audio Transformer | Soundwaves | Wave Forms