This paper describes a strategy followed by the dialogue manager of a database inquiry system to assess the reliability of input utterances. For this purpose, binary classification trees are used, in such a way that the assessment capability can be automatically learnt from samples. As a starting point, training of such trees for classification of ATIS-3 sentences in terms of A, D, and X classes was done; experimental results show that this assessment technique can be effectively exploited and integrated into the dialogue manager under development.
Cite as: Cettolo, M., Corazza, A., Mori, R.D. (1995) Automatic learning of sentence dependencies in spoken dialogues. Proc. ESCA Workshop on Spoken Dialogue Systems, 77-80
@inproceedings{cettolo95_sds,
author={Mauro Cettolo and Anna Corazza and Renato De Mori},
title={{Automatic learning of sentence dependencies in spoken dialogues}},
year=1995,
booktitle={Proc. ESCA Workshop on Spoken Dialogue Systems},
pages={77--80}
}