8th European Conference on Speech Communication and Technology

Geneva, Switzerland
September 1-4, 2003


Combination of Finite State Automata and Neural Network for Spoken Language Understanding

Chai Wutiwiwatchai, Sadaoki Furui

Tokyo Institute of Technology, Japan

This paper proposes a novel approach for spoken language understanding based on a combination of weighted finite state automata and an artificial neural network. The former machine acts as a robust parser, which extracts some semantic information called subframes from an input sentence, then the latter machine interprets a concept of the sentence by considering the existence of subframes and their scores obtained from the automata. With a large number of concepts handled in our mixed-initiative dialogue system, the proposed system achieves a considerable concept interpretation result on either a typed-in test set or a spoken test set. A high subframe recall rate also verifies an applicability of the proposed system.

Full Paper

Bibliographic reference.  Wutiwiwatchai, Chai / Furui, Sadaoki (2003): "Combination of finite state automata and neural network for spoken language understanding", In EUROSPEECH-2003, 2761-2764.