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The popular music streaming service is looking in to new ways to make better song recommendations based on a varitey of factors such as users’ motion, heart beat, temperature, and maybe even sleep patterns. For the new feature, sensors would be placed on the listener’s body or in their smartphone to gather this important information.
Spotify hopes to select even more appropriate music by taking all these factors in to account, including them in its already complex algorithm. Spotify product manager for discovery and recommendations, Donovan Sung, explained the company’s motivation for the new feature: “Maybe with motion sensors in phones, we can start guessing things whether users are running, biking, or driving? Maybe the phone has a temperature sensor, or a heart rate sensor, we could guess whether the user is tense…”
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The information generated by these sensors could be used to create playlists based on the user’s activities, from workouts and driving to late-night working and sleeping. It could even predict when to automatically start playing pumping music when it’s time for the user to exercise or play more peaceful music when it’s time to go to sleep.
“The more we know about you, the better the recommendation engine can be,” claimed Sung, who also stressed the importance of striking the perfect balance between the quantity and quality of recommendations on Spotify.
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