Video content discovery solutions provider Jinni, unveiled today at CES 2013 a radically new NLU (natural language understanding) discovery engine to power the first voice-activated video guides that understand natural human language. Until now, the voice-activated TV experience was limited to basic commands because that was all the guide could process. The Jinni NLU engine leverages the company’s unique Entertainment Genome™ to interpret natural human speech and derive the underlying meaning to enable rich, intuitive interaction between users and their TVs. Now users will be able to simply tell their TV what they are in the mood to watch and Jinni will find the most fitting content from live TV, VOD and any other available video catalog.
Jinni’s NLU engine enables a truly natural, intuitive user experience. Simply tell the TV want you want, for example:
- “Is there anything witty and romantic on TV tonight?”
- “Show us something like Dexter on VOD.”
- “I want to watch something funny about an obnoxious boss.”
“Consumer demand has changed dramatically and today people expect to be able to interact with technology in a very natural, personalized way,” explained Jinni co-founder and CEO, Yosi Glick. “This is the core belief that inspired our semantic approach to video discovery and has allowed us to bring such an advanced NLU solution to market so quickly.”
The Jinni gene-based discovery solution has differentiated itself from other engines by taking content analysis and unique user-centric recommendations to the next level – with natural language understanding capabilities, Jinni meets the growing consumer demand for a semantic cross-platform experience.
Jinni is the first and only taste-and-mood based engine powering entertainment discovery. Using content genetics and nuanced understanding of user tastes, the Jinni engine powers a uniquely intuitive and personalized experience that increases content consumption and consumer satisfaction.
The Jinni service is powered by the Entertainment Genome, containing thousands of genes that are assigned to each title to describe mood, style, plot, setting and more; this is a rich alternative to the usual genre language, which benefits both the quality of the content delivered as well as the intuitive semantic-based user experience. New titles are automatically indexed via analysis of user reviews and synopses, using a proprietary Natural Language Processing solution.
Jinni’s content discovery solution has been voted “Best Product Idea” by CableLabs. Jinni is a Webby Awards honoree, a Red Herring 100 Europe winner, an OnHollywood 100 winner, a SXSW Web Awards nominee, a TechCrunch Europas nominee, a finalist in the 2012 Connected TV Awards for Outstanding Technology Innovation, and was selected as the best movie recommendation engine by CNET and Lifehacker. Jinni provides content discovery and recommendation solutions to European content providers Belgacom and Prisa TV. To see Jinni's award winning engine at work, visit www.jinni.com.