https://www.livescience.com/health/...c-you-listened-to-based-on-your-brain-signals
By examining a person's brain activity, artificial intelligence (AI) can produce a song that matches the genre, rhythm, mood and instrumentation of music that the individual recently heard.
Scientists have previously "reconstructed" other sounds from brain activity, such as
human speech, bird song and horse whinnies. However, few studies have attempted to recreate music from brain signals.
Now, researchers have built an AI-based pipeline, called Brain2Music, that harnesses brain imaging data to generate music that resembles short snippets of songs a person was listening to when their brain was scanned. They described the pipeline in a paper, published July 20 to the preprint database
arXiv, which has not yet been peer-reviewed.
The AI was customized for each person, drawing links between their unique brain activity patterns and various musical elements.
After being trained on a selection of data, the AI could convert the remaining, previously unseen, brain imaging data into a form that represented musical elements of the original song clips. The researchers then fed this information into another AI model previously developed by Google, called
MusicLM. MusicLM was originally developed to generate music from text descriptions, such as "a calming violin melody backed by a distorted guitar riff."
MusicLM used the information to generate
musical clips that can be listened to online and fairly accurately resembled the original song snippets — although the AI captured some features of the original tunes much better than others.
Interestingly, a past study found that the activity of different parts of the prefrontal cortex
dramatically shifts when freestyle rappers improvise.
Future studies could explore how the brain processes music of different genres or moods. The team also hopes to explore whether AI could reconstruct music that people are only imagining in their heads, rather than actually listening to.
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