Corpora and Machine Translation Harold Somers


Rapid development of MT for less-studied languages



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Rapid development of MT for less-studied languages


An important attraction of corpus-based MT techniques is the possibility that they can be used to quickly develop MT systems for less-studied languages (cf. Chapter Article 23), inasmuch as these MT techniques require only bilingual corpora and appropriate tools for alignment, extraction of linguistic data and so on. It must be said that some of the latest ideas, particularly in SMT, requiring treebanks and parsers make this less relevant. Nevertheless, empiriacala methods do seem to embody the best hoper for resourcing under-resourced languages.

The first such attempt to demonstrate the feasibility of this was at the Johns Hopkins Summer Workshop in 1999, when students built a Chinese–English SMT system in one day (Al-Onizan et al. 1999). Although Chinese is not a less-studied language as such, it is of interest because English and Chinese are typologically quite dissimilar. The corpus used was the 7 million-word “Hong Kong Laws” corpus and the system was built using the EGYPT SMT toolkit developed at the same workshop and now generally available online.

Germann (2001) tried similar techniques with rapidly developed resources, building a Tamil–English MT system by manually translating 24,000 words of Tamil into English in a six week period. Weerasinghe (2002) worked on Sinhala–English using a 50,000-word corpus from the World Socialist Web Site. Oard and Och (2003) built a system to translate between English and the Philippine language Cebuano, based on 1.3m words of parallel text collected from five sources (including Bible translations and on-line and hard-copy newsletters). Foster et al. (2003) describe a number of difficulties in their attempt to build a Chinese–English MT system in this way.

6.Conclusions


MT is often described as the historically original task of Nnatural Llanguage Pprocessing, as well as the archetypical task in that it has a bit of everything, indeed in several languages; so it is no surprise that corpora – or at least collections of texts – have played a significant role in the history of MT. However, it is only in the last 10–15 years that they have really come to the fore with the emergence and now predominance of corpus-based techniques for MT. This chapter article has reviewed that history, from “reference corpora” in the days of rule-based MT via corpus-based translators’ tools, to MT methods based exclusively on corpus information. Many of the tools developed for corpus exploitation and described in other chapters in this book have had their genesis in MT, and research in corpus-based MT is certainly at the forefront of computational linguistics at the moment.

7.Acknowledgments

I would like to thank the editors and an anonymous reviewer for their very helpful comments on earlier drafts of this article. I would also like to thank Andy Way for his advice and suggestions on several sections of this article. All errors and infelicities remain of course my own responsibility.

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Maria no daba una bofetada a la bruja verda

Maria




























did




























not




























slap




























the




























green




























witch




























Figure 1. Initial phrasal alignment for example (22)




Maria no daba una bofetada a la bruja verda

Maria




























did




























not




























slap




























the




























green




























witch




























Figure 2. Further phrasal identification

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