Breakthrough: New technology can match songs to your changing moods

Have you ever wondered if there is a personalised DJ system for you that matches songs to your changing moods? How exciting would that be? Well, now researchers have developed something similar. Computer scientists have developed a new "DJ-like" algorithm that can create personalised music playlists that adapt to listeners' changing moods. The algorithm is called DJ-MC. Such a system could probably even beat music streaming services in the future with its ability to make playlists that can change depending on your shifting emotion, according to the research published in the journal MIS Quarterly.

"Whether you're getting into the car after a long day of meetings, or you're getting out of bed on a weekend morning, it should tailor its recommendations to your changing moods," said Maytal Saar-Tsechansky, a professor at the University of Texas (UT) at Austin in the US.

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The programme runs a series of feedback loops. It tries out a song, the listener rates it, and the programme heeds that rating in choosing the next song.

"Then you alter the model accordingly," said Elad Liebman, a PhD student in computer science at UT Austin, who conceptualised the programme.

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How it works

DJ-MC adapts to the listener's mood, considering not only which songs they will enjoy, but also in what order, the researchers said. Songs are organised intelligently, leading to an expressive, 'DJ-like' sequence, instead of a random, arbitrary-sounding one, they said. According to the researchers, DJ MC plans its moves 10 songs ahead, like a chess player. While one song is playing, the programme generates tens of thousands of possible sequences, and it predicts which one will please the listener the most, they said. The programme serves up the next song on that playlist -- and while that song is playing, it creates and tests new sequences. The researchers noted that in machine learning, the mechanism is known as a Monte Carlo search which inspired the name of the programme: DJ-MC. The programme could be adapted to other kinds of media, from news stories to videos, they said.

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"Learning algorithms don't have taste, they just have data. You can replace the dataset with anything, as long as people are consuming it in a similar fashion," Liebman said.

(With PTI inputs)

Picture: Pixabay (For the representational purpose)