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Hybrid Natural Language Generation from Lexical Conceptual Structures

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Machine Translation

Abstract

This paper describes Lexogen, a system for generating natural-languagesentences from Lexical Conceptual Structure, an interlingualrepresentation. The system has been developed as part of aChinese–English Machine Translation (MT) system; however, it isdesigned to be used for many other MT language pairs and naturallanguage applications. The contributions of this work include: (1)development of a large-scale Hybrid Natural Language Generation system withlanguage-independent components; (2) enhancements to an interlingualrepresentation and associated algorithm forgeneration from ambiguous input; (3) development of an efficientreusable language-independent linearization module with a grammardescription language that can be used with other systems; (4)improvements to an earlier algorithm forhierarchically mapping thematic roles to surface positions; and (5)development of a diagnostic tool for lexicon coverage and correctnessand use of the tool for verification of English, Spanish, and Chineselexicons. An evaluation of Chinese–English translation quality showscomparable performance with a commercial translation system. Thegeneration system can also be extended to other languages and this isdemonstrated and evaluated for Spanish.

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Authors and Affiliations

  1. Institute for Advanced Computer Studies, University of Maryland, College Park, MD, 20742, USA E-mail

    Nizar Habash & Bonnie Dorr

  2. University of Southern California Institute for Creative Technologies, 13274 Fiji Way, Marina del Rey, CA, 90292, USA E-mail

    David Traum

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  1. Nizar Habash
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Habash, N., Dorr, B. & Traum, D. Hybrid Natural Language Generation from Lexical Conceptual Structures. Machine Translation 18, 81–128 (2003). https://doi.org/10.1023/B:COAT.0000020960.27186.18

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