An intelligent TV interface based on statistical dialogue management

In this paper, we propose an intelligent TV interface using a voice-enable dialogue system. This paper rests on the both directions: a new type of dialogue management model and its use for practical systems to commercialize. We devise a practical dialogue management model based on statistical learning methods. To analyze discourse context, we utilize statistical learning techniques for anaphora resolution and discourse history management. Contrary to the rule-based system, we develop an incremental learning method to construct dialogue strategies from the training corpus. Several dialogue service models equipped with the proposed TV interface are explained. To evaluate our model and its impact on an application task, we apply the stand-alone model to an TV settop box called eDi-TV.