Why it matters: A recent study at Claremont Graduate University has applied machine learning to neurophysiological data, identifying hit songs with an astonishing 97% accuracy.
Read more: ‘Neuroforecasting’: How science can predict the next hit song with 97% accuracy.
Read the Research article.
Discussion on Hacker News.
Surveys After each song, participants were asked to rank how much they liked the song (1 to 10), if they would replay the song (0, 1), recommend the song to their friends (0, 1), if they had heard it previously to assess familiarity (0, 1), and if they found the song offensive (0, 1). We also showed participants lyrics from the song and lyrics created by the researchers and asked them to identify the song lyrics to measure their memory of the song (0, 1).
I still think your concern is legitimate.
Memory is funny. Stuff can play in the background and become familiar without you being consciously aware of it.
It would be possible to do this study without contamination by using completely unknown and newly-released songs as a dataset, and checking against future chart data regarding the popularity, or by examining the reaction of an isolated group of people without constant musical bombardment.
It would be possible to do this study without contamination by using completely unknown and newly-released songs
When writing songs, I always wondered if that genius idea is actually just something I heard 10 years ago, but don’t remember consciously. Similarly, I wonder if I like a catchy tune because it is catchy in itself, or because it reminds me of something which I cannot recall consciously right now.
Sometimes, I had these moments later when the dots connect, sometimes not. With what confidence could I conclude something is new and original?
I guess that’s just another task for future AI.