Preface. (15th June 2016)

• Record Type: Journal Article
• Authors: RAPP, REINHARD; SHAROFF, SERGE; ZWEIGENBAUM, PIERRE
• Editors: Rapp, Reinhard; Sharoff, Serge; Zweigenbaum, Pierre
• Is Part Of: Natural language engineering. Volume 22:Part 4(2016)
• Page Start: 497
• Page End: 500
• Publication Date: 2016-06-15
• Subjects: Natural language processing (Computer science) -- Periodicals; Software engineering -- Periodicals; 006.35
• DOI: 10.1017/S1351324916000103
• Languages: English
• ISSNs: 1351-3249

Abstract

Abstract : After several decades of work on rule-based machine translation (MT) where linguists try to manually encode their knowledge about language, the time around 1990 brought a paradigm change towards automatic systems which try to learn how to translate by looking at large collections of high-quality sample translations as produced by professional translators. The first such attempts were called example- or analogy-based translation, and somewhat later the so-called statistical approach to MT was introduced. Both can be subsumed under the label data-driven approaches to MT . It took about 10 years until these self-learning systems became serious competitors of the traditional rule-based systems, and by now some of the most successful MT systems, such as Google Translate and Moses, are based on the statistical approach.