OpenAI this week released Jukebox, a machine learning framework that generates music — including rudimentary songs — as raw audio in a range of genres and musical styles. From a report: Provided with a genre, artist, and lyrics as input, Jukebox outputs a new music sample produced from scratch. The code and model are available on GitHub, along with a tool to explore the generated samples. Jukebox might not be the most practical application of AI and machine learning, but as OpenAI notes, music generation pushes the boundaries of generative models. Synthesizing songs at the audio level is challenging because the sequences are quite long — a typical 4-minute song at CD quality (44 kHz, 16-bit) has over 10 million timesteps. As a result, learning the high-level semantics of music requires models to deal with very long-range dependencies.
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