This paper describes a method for building statistical Language Models (LMs) dedicated to specific dialogue situations. The architecture of the speech recognition system proposed uses several LMs. The first stage of this system, consists of producing a word-lattice from a given sentence uttered by a speaker. A general LM calculates a sentence-hypothesis. Then, in a second stage, the system chooses a specialized LM according to the word-lattice and the previous hypothesis. Another decoding process is performed using this specialized LM in order to produce a new sentence- hypothesis. Finally, a decision-module processes these two hypotheses in order to assign three confidence levels to the sentence-hypothesis produced. These confidence levels can be used by the dialogue manager in order to improve the dialogue, by asking a confirmation to the speaker when a sentence is labeled ambiguous.
Cite as: Estève, Y., Béchet, F., Mori, R.d. (2000) Dynamic selection of language models in a dialogue system. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 1, 214-217, doi: 10.21437/ICSLP.2000-53
@inproceedings{esteve00_icslp,
author={Yannick Estève and Frédéric Béchet and Renato de Mori},
title={{Dynamic selection of language models in a dialogue system}},
year=2000,
booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
pages={vol. 1, 214-217},
doi={10.21437/ICSLP.2000-53}
}