Multilingual semantic parsing and code-switching

Long Duong, Hadi Afshar, Dominique Estival, Glen Pink, Philip Cohen, Mark Johnson

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Downloads (Pure)

Abstract

Extending semantic parsing systems to new domains and languages is a highly expensive, time-consuming process, so making effective use of existing resources is critical. In this paper, we describe a transfer learning method using crosslingual word embeddings in a sequence-to-sequence model. On the NLmaps corpus, our approach achieves state-of-the-art accuracy of 85.7% for English. Most importantly, we observed a consistent improvement for German compared with several baseline domain adaptation techniques. As a by-product of this approach, our models that are trained on a combination of English and German utterances perform reasonably well on code-switching utterances which contain a mixture of English and German, even though the training data does not contain any such. As far as we know, this is the first study of code-switching in semantic parsing. We manually constructed the set of code-switching test utterances for the NLmaps corpus and achieve 78.3% accuracy on this dataset.
Original languageEnglish
Title of host publicationProceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)
Place of PublicationStroudsburg, PA
PublisherAssociation for Computational Linguistics
Pages379-389
Number of pages11
ISBN (Electronic)9781945626548
DOIs
Publication statusPublished - 2017
Externally publishedYes
EventConference on Computational Natural Language Learning (21st : 2017) - Vancouver, Canada
Duration: 3 Aug 20174 Aug 2017

Conference

ConferenceConference on Computational Natural Language Learning (21st : 2017)
Abbreviated titleCoNLL 2017
CountryCanada
CityVancouver
Period3/08/174/08/17

Bibliographical note

Copyright the Publisher 2017. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Fingerprint Dive into the research topics of 'Multilingual semantic parsing and code-switching'. Together they form a unique fingerprint.

Cite this