Multilingual Spoken Language Understanding using graphs and multiple translations

被引：7

作者：

Calvo, Marcos ^{[1
]}

Hurtado, Lluis-Felip ^{[1
]}

Garcia, Fernando ^{[1
]}

Sanchis, Emilio ^{[1
]}

Segarra, Encarna ^{[1
]}

机构：

[1] Univ Politecn Valencia, Dept Sistemes Informat & Comp, Cami de Vera S-N, Valencia 46020, Spain

来源：

COMPUTER SPEECH AND LANGUAGE | 2016年 / 38卷

关键词：

Multilingual Language Understanding; Graph of words; Graph of concepts; Statistical semantic models; PORTABILITY; NETWORKS;

D O I：

10.1016/j.csl.2016.01.002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present an approach to multilingual Spoken Language Understanding based on a process of generalization of multiple translations, followed by a specific methodology to perform a semantic parsing of these combined translations. A statistical semantic model, which is learned from a segmented and labeled corpus, is used to represent the semantics of the task in a language. Our goal is to allow the users to interact with the system using other languages different from the one used to train the semantic models, avoiding the cost of segmenting and labeling a training corpus for each language. In order to reduce the effect of translation errors and to increase the coverage, we propose an algorithm to generate graphs of words from different translations. We also propose an algorithm to parse graphs of words with the statistical semantic model. The experimental results confirm the good behavior of this approach using French and English as input languages in a spoken language understanding task that was developed for Spanish. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：86 / 103

页数：18

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