Source language diagnostics for MT

Teruko Mitamura, Kathryn Baker, David Svoboda, Eric Nyberg


Abstract
This paper presents a source language diagnostic system for controlled translation. Diagnostics were designed and implemented to address the most difficult rewrites for authors, based on an empirical analysis of log files containing over 180,000 sentences. The design and implementation of the diagnostic system are presented, along with experimental results from an empirical evaluation of the completed system. We found that the diagnostic system can correctly identify the problem in 90.2% of the cases. In addition, depending on the type of grammar problem, the diagnostic system may offer a rewritten sentence. We found that 89.4% of the rewritten sentences were correctly rewritten. The results suggest that these methods could be used as the basis for an automatic rewriting system in the future.
Anthology ID:
2003.mtsummit-papers.34
Volume:
Proceedings of Machine Translation Summit IX: Papers
Month:
September 23-27
Year:
2003
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New Orleans, USA
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MTSummit
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URL:
https://aclanthology.org/2003.mtsummit-papers.34
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Cite (ACL):
Teruko Mitamura, Kathryn Baker, David Svoboda, and Eric Nyberg. 2003. Source language diagnostics for MT. In Proceedings of Machine Translation Summit IX: Papers, New Orleans, USA.
Cite (Informal):
Source language diagnostics for MT (Mitamura et al., MTSummit 2003)
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https://aclanthology.org/2003.mtsummit-papers.34.pdf