Paper: Exploiting multiple hypotheses for Multilingual Spoken Language Understanding

ACL ID W13-3521
Title Exploiting multiple hypotheses for Multilingual Spoken Language Understanding
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2013
Authors

In this work, we present an approach for multilingual portability of Spoken Lan- guage Understanding systems. The goal of this approach is to avoid the effort of ac- quiring and labeling new corpora to learn models when changing the language. The work presented in this paper is focused on the learning of a specific translator for the task and the mechanism of transmitting the information among the modules by means of graphs. These graphs represent a set of hypotheses (a language) that is the input to the statistical semantic decoder that pro- vides the meaning of the sentence. Some experiments in a Spanish task evaluated with input French utterances and text are presented. They show the good behavior of the system, mainly when speech input is considered.