Context-Aware Proactive Personalization of Linear Audio Content

How many times did you wish the radio programming was more aligned with your interests or current situation? How many times did you feel the need to change the channel because of a non-interesting content on your favorite station? Did you ever feel distracted by the audio programming in your car at a busy intersection? We present a platform for proactive personalization of linear audio content within a hybrid content radio framework. Hybrid content radio programming aims at enhancing the traditional broadcast radio experience and augmenting it with audio content related to the listener’s context. It allows enrichment of the broadcaster’s program schedule with context-aware, personalized audio content, with the goal of improving the users’ listening experience, decreasing their propensity to channel-surf, and giving them more targeted content, such as local news, entertainment, music and also relevant advertisements. Differently from most of the popular commercial recommendation-based streaming music services, hybrid content radio systematically and automatically adds audio content to an existing, linear audio structure. More specifically, part of the linear content is replaced, in a proactive way, with content relevant to the user’s current context – i.e., profile, emotional state, activity, geographical position, weather, or other factors contributing to the state of the listener. In addition to enabling functional enhancement of the radio experience, the presented framework also supports network resource optimization, allowing effective use of the broadcast channel and the Internet.