Google's new AI tool can now create music of any genre from text prompts and even transcribe a melody into other instruments when it is hummed or whistled. The newly launched technique, called MusicLM is a text-to-music creation system, claims Google Research. The AI tool functions by examining the text and figuring out how large and intricate the composition is.
"We introduce MusicLM, a model generating high-fidelity music from text descriptions such as a calming violin melody backed by a distorted guitar riff'," the research paper mentions. It further added, "We demonstrate that MusicLM can be conditioned on both text and a melody in that it can transform whistled and hummed melodies according to the style described in a text caption,". The research paper claims that the new artificial intelligence has been trained on a dataset of 280,000 hours of music in order to learn how to create songs that make sense from text descriptions and to pick up subtleties like mood, melody, and instruments. More than only creating song clips is possible with it. It was demonstrated by Google researchers that the algorithm can build on current tunes, whether they be whistled, hummed, sung, or played on an instrument.
In addition, the research shows that Google's new AI tool can take a series of written descriptors, such as "time to meditate," "time to wake up," "time to run," and "time to give 100%," and turn them into a melodic "story" or narrative that can last for several minutes. Additionally, Google's new AI tool may be directed by a picture and caption combination, or it may produce audio that is "played" by a certain kind of instrument in a particular game. Google is not the first business to do this, it should be noted. According to TechCrunch, initiatives like Google's AudioLM, OpenAI's Jukebox, or Riffusion—an AI that can create music by seeing it—have all made an attempt. However, none have been able to produce songs that are extremely complicated in the composition of high-fidelity due to technical restrictions and a lack of training data. So, according to researchers, MusicLM may be the first to be able to do so.
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