Turn-based language modeling for spoken dialog systems

Abstract

In this paper, we propose a turn-based language modeling (TurnLM) technique for spoken dialog systems. This technique utilizes the time dependent nature of a dialog aimed at accomplishing a task. As opposed to the dialog state based language modeling techniques which depend on the information in the system prompt, TurnLM does not require any information from the dialog manager. As such, TurnLM can be used not only for human-machine dialogs but also human-human dialogs. We report performance improvement compared to the baseline system on the IBM DARPA Communicator spoken dialog system. Experimental results also suggest that TurnLM is a viable alternative to dialog state based language modeling technique.