Sci-tech

Spotify Wants To Recommend Songs Based On Users' Emotions

Spotify Wants To Recommend Songs Based On Users' Emotions”

Spotify also has an algorithm already in place that suggests new audio content for users based on their previous listening habits, so the want to add more variations to gauge what the user might be interested in listening to is not surprising.

The patent for "Identification of taste attributes from an audio signal", as the invention is called, was filed in February 2018, and granted on January 12 of this year, Music Business Worldwide reported.

Spotify has earlier patented another technology that can recommend music to users based on their personal traits.

Spotify will take this into consideration alongside listening history, library, followed artists, and more to fine-tune it's song recommendations.

The patent suggests obtaining "intonation, stress, rhythm and the likes of units of speech" could be combined with "acoustic information within a hidden Markov model architecture" so that Spotify's app could categorize a user's mood as "happy, angry, sad or neutral".

The patent claimed it can even create a playlist based on detecting by background noises, for example, if the user is alone, with others or at a party.

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A closer look at the patent reveals an overview of how Spotify now use a decision tree in order to tailor its content recommendation algorithm to each user, with the streaming giants stating that by eliminating human input, the algorithm will function far more effectively.

"A system, method and computer product are provided for processing audio signals". It could then also utilize other information it may have about the user, including their "gender, age and accent".

The result is a huge collection of data that can be used to provide users recommended tracks to be played next.

The patent filing by Spotify indicates the way brands are looking to user in personalization 2.0, where services are reacting in real-time not just to the sequence and timing of buttons we press on devices, but on data collected from our immediate environments and biometrics.

You can read the patent here.



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