Browsing Articles (ISV) by Title
Previous Page
Now showing items 3-4 of 4
-
Low Resources Machine TranslationCarl, Michael; Maite, Melero; Badia, Toni; Vandeghinste, Vincent; Dirix, Peter; Schuurman, Ineke; Markantonatou, Stella; Sofianopoulos, Sokratis; Vassiliou, Marina; Yannoutsou, Olga (, 2008)[More information][Less information]
Abstract: METIS-II was a EU-FET MT project running from October 2004 to September 2007, which aimed at translating free text input without resorting to parallel corpora. The idea was to use ‘basic’ linguistic tools and representations and to link them with patterns and statistics from the monolingual target-language corpus. The METIS-II project has four partners, translating from their ‘home’ languages Greek, Dutch, German, and Spanish into English. The paper outlines the basic ideas of the project, their implementation, the resources used, and the results obtained. It also gives examples of how METIS-II has continued beyond its lifetime and the original scope of the project. On the basis of the results and experiences obtained, we believe that the approach is promising and offers the potential for development in various directions. URI: http://hdl.handle.net/10398/8037 Files in this item: 1
METIS-II.pdf (503.5Kb) -
Quantifying alignment units with keystroke dataCarl, Michael (, 2009)[More information][Less information]
Abstract: The paper discusses a method to triangulate process and product data. We suggest converting Translog data into a relational format which contains both process and product data. We outline how this representation allows us to retrieve and correlate the various dimensions of the data more easily. The concept of Alignment Unit (AU) is introduced and contrasted with that of Translation Unit (TU). While AUs refer to translation equivalences in the source and target texts of the product data, TUs refer to cognitive entities that can be observed in the process data. With an (almost) exhaustive fragmentation of the source and target texts into AUs, we are able to distribute and allocate the entire set of keystroke data to appropriate AUs. Using the properties of the keystroke data, AUs are quantified in a novel way which enables us to visualise and investigate the structure of translation production on a fine-grained scale. URI: http://hdl.handle.net/10398/8040 Files in this item: 1
keystrokes.pdf (940.0Kb)
Previous Page
Now showing items 3-4 of 4