Spoken Language Understanding strategies on the France Telecom 3000 voice agency corpus

Telephone services are now deployed that allow users to react to telephone prompts in spoken natural language. These systems have limited domain semantics and dialogue strategies which are represented by finite state diagrams. Most of these systems adopt a sequential approach where the Automatic Speech Recognition (ASR) process, the Spoken Language Understanding (SLU) process and the Dialogue Management (DM) are separate processes. In the framework of the France Telecom 3000 voice service, we propose in this paper to study several strategies in order to integrate more closely these three processes: ASR, SLU, and DM. By means of a Finite State Machine paradigm encoding the different models used by these three levels we show how the search for the best sequence of dialogue states can be done simultaneously at the word, concept, interpretation and dialogue state levels.