Computer Can Predict Whether A Song Will Be Hit Or Not

As people’s taste for music and song differ from each other, hence only they can decide, which song or what type of music they’ll like and which they don’t. But, it seems time has come to change that trend. A recent article published in Scientific Reports showed that computers can be used to predict how popular a particular song would be, and whether a listener would like it or not.


How is it possible that a computer can understand a people’s musical taste? The computer will do this by analyzing the musical characteristics of past music listening trends. For doing so, there’ll be a special program in the computer. Through the program, the computer will try to find out what type of music people liked most. After finding out, the computer will be able to predict easily whether a new song would be popular to people or not.

Some Spanish Researchers conducted this experiment through analyzing 464,411 Western Pop Music between 1955-2010 including hip-hop, folk, pop, rock, and funk. They analyzed the music by –

  • discerning relationship patterns between the data pieces,
  • “slicing up” the music into little data pieces,
  • classifying the data pieces with regard to pitch, timbre, and volume, and
  • discerning which data pieces and relationships were trending.

The authors (researchers) of this study found, through the computer program, that the popularity of Pop Music were decreased gradually due to poor quality. According to researchers musicians at that time couldn’t understand people’s musical taste.

However, it’s being assumed that in near future, computers will play a significant role in determining what music or song people will love to listen what they won’t. You can say, the computer will play a significant role as a music critic.

Source : Scientific Reports
Thanks To : New York Times

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Anatol

Anatol Rahman is the Editor at TheTechJournal. He loves complicated machineries, and crazy about robot and space. He likes cycling. Before joining TheTechJournal team, he worked in the telemarketing industry. You can catch him on Google+.

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