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Erschienen in:
Jointly Modeling Intent Identification and Slot Filling with Contextual and Hierarchical Information Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Using Bilingual Segments to Improve Interactive Machine Translation

verfasst von : Na Ye, Ping Xu, Chuang Wu, Guiping Zhang

Erschienen in: Natural Language Processing and Chinese Computing

Verlag: Springer International Publishing

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Abstract

Recent research on machine translation has achieved substantial progress. However, the machine translation results are still not error-free, and need to be post-edited by a human translator (user) to produce correct translations. Interactive machine translation enhanced the human-computer collaboration through having human validate the longest correct prefix in the suggested translation. In this paper, we refine the interactivity protocol to provide more natural collaboration. Users are allowed to validate bilingual segments, which give more direct guidance to the decoder and more hints to the users. Besides, validating bilingual segments is easier than identifying correct segments from the incorrect translations. Experimental results with real users show that the new protocol improved the translation efficiency and translation quality on three Chinese-English translation tasks.

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Vorheriges Kapitel Research on Mongolian Speech Recognition Based on FSMN
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Metadaten
Titel
Using Bilingual Segments to Improve Interactive Machine Translation
verfasst von
Na Ye
Ping Xu
Chuang Wu
Guiping Zhang
Copyright-Jahr
2018
Buch
Natural Language Processing and Chinese Computing

Print ISBN: 978-3-319-73617-4

Electronic ISBN: 978-3-319-73618-1

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-73618-1_22