Abstract
Systems and techniques are proposed that provide an improved experience for a user when interacting with a television (TV) application running on a media player. The TV application may interface with media content providers to fetch media content for streaming to and viewing on the media player by way of the internet. The media player may be a computing device (e.g., a Smart TV, a tablet computer, a smart phone, a laptop computer, a mobile computing device) connected to a network and interfaced to the internet.
The TV application may receive media content recommendations from a recommendation engine. The recommendation engine may generate media content recommendations using models that can interpret information and data received from a user of the TV application. The received information may be input information and data received from multiple sources and in multiple formats. The input information and data may include, but is not limited to, audio input, voice input, text input, gesture input, video input, and input images.
Basing media content recommendations on models that can interpret the information and data received from the user of the TV application enables the user to receive recommendations for media content that are finetuned and more focused on the interests of the user, for example, at a particular time and place, and with a particular audience.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Nayak, Shravan; Chatterjee, Tamojit; Murugesan, Sundaramoorthy; Kanchu, Venkata Gangadhar; Niranjan, Kopal; Sharma, Priyanshi; and Mishra, Kanishka, "Multimodal Based Television Recommendation", Technical Disclosure Commons, (December 29, 2024)
https://www.tdcommons.org/dpubs_series/7687