Anticipatory translation model adaptation for bilingual conversations

Sanjika Hewavitharana, Dennis Mehay, Sankaranarayanan Ananthakrishnan, Rohit Kumar, John Makhoul


Abstract
Conversational spoken language translation (CSLT) systems facilitate bilingual conversations in which the two participants speak different languages. Bilingual conversations provide additional contextual information that can be used to improve the underlying machine translation system. In this paper, we describe a novel translation model adaptation method that anticipates a participant’s response in the target language, based on his counterpart’s prior turn in the source language. Our proposed strategy uses the source language utterance to perform cross-language retrieval on a large corpus of bilingual conversations in order to obtain a set of potentially relevant target responses. The responses retrieved are used to bias translation choices towards anticipated responses. On an Iraqi-to-English CSLT task, our method achieves a significant improvement over the baseline system in terms of BLEU, TER and METEOR metrics.
Anthology ID:
2014.iwslt-papers.11
Volume:
Proceedings of the 11th International Workshop on Spoken Language Translation: Papers
Month:
December 4-5
Year:
2014
Address:
Lake Tahoe, California
Editors:
Marcello Federico, Sebastian Stüker, François Yvon
Venue:
IWSLT
SIG:
SIGSLT
Publisher:
Note:
Pages:
230–235
Language:
URL:
https://aclanthology.org/2014.iwslt-papers.11
DOI:
Bibkey:
Cite (ACL):
Sanjika Hewavitharana, Dennis Mehay, Sankaranarayanan Ananthakrishnan, Rohit Kumar, and John Makhoul. 2014. Anticipatory translation model adaptation for bilingual conversations. In Proceedings of the 11th International Workshop on Spoken Language Translation: Papers, pages 230–235, Lake Tahoe, California.
Cite (Informal):
Anticipatory translation model adaptation for bilingual conversations (Hewavitharana et al., IWSLT 2014)
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PDF:
https://aclanthology.org/2014.iwslt-papers.11.pdf