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Canela.TV Adopts A.I. Tech to Determine the ‘Mood’ of Content

Canela.TV
(Image credit: Canela.TV)

NEW YORK CITY—How many times have TV viewers told family members and friends something like: “I feel like watching football,” or “I feel like watching a soap opera” or “I feel like watching the news?”

Canela.TV, a provider of AVOD streaming services for U.S. Hispanics, is taking the feeling aspect of content selection to a whole new level thanks to an expanded partnership with Vionlabs. Leveraging the company’s technology, Canela.TV will enable subscribers to select content based on the emotions evoked by every program in its library, the streaming service said.

The service is deploying Vionlabs’ Moods, part of its Fingerprint+ product offering. Moods uses A.I. to analyze video metadata to extract relevant information to determine the emotional impact of content at scale, Canela.TV said.

Using Moods, the streaming service can automatically generate mood labels, mood time series and mood values for every piece of content in its library and ultimately give viewers information that can help them match their emotional state to the emotional characteristics of specific programming.

"Consuming digital content is an emotional investment by the end user, so for Canela.TV to understand the mood of video content makes perfect sense," said Marcus Bergström, CEO of Vionlabs.

"Choosing something to watch can sometimes be a daunting task, being able to sort content based on how you're feeling is something new and different for Canela.TV users and takes the guesswork out of choosing entertainment options," he continued. 

Canela.TV’s partnership with Vionlabs is “the first and only” one in the United States that takes Moods live.

More information is available on the Canela.TV and Vionlabs websites.

Phil Kurz is a contributing editor to TV Tech. He has written about TV and video technology for more than 30 years and served as editor of three leading industry magazines. He earned a Bachelor of Journalism and a Master’s Degree in Journalism from the University of Missouri-Columbia School of Journalism.