Abstract
This paper presents the implementation part of my doctoral research at the University of Cambridge. It provides a description of the Information Structure Transfer (IST), a machine translation prototype designed within the framework of the Spoken Language Translator (SLT by SRI, Cambridge/Palo Alto) and based on the Core Language Engine ([1]). The IST includes two discourse-processing modules: the pre-transfer Information Structure Activator (ISA) and the post-transfer Information Structure Generator (ISG). The IST prototype calculates and processes vital features of information structure explored in context of structural differences between positional and nonpositional languages. It offers algorithmic solutions and an implementation framework for local discourse processing in machine translation. Under scrutiny is a web of interrelated factors such as pronominalization, anaphora resolution, zero anaphors, definiteness and constituent order.
Keywords
- Machine Translation
- Interrelated Factor
- Transfer Rule
- Anaphora Resolution
- Constituent Order
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Budzikowska, M. (2000). Information Structure Transfer: Bridging the Information Gap in Structurally Different Languages. In: White, J.S. (eds) Envisioning Machine Translation in the Information Future. AMTA 2000. Lecture Notes in Computer Science(), vol 1934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39965-8_8
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DOI: https://doi.org/10.1007/3-540-39965-8_8
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