Year: 2009
Type: report
Abstract: Phrase-Based Statistical Machine Translation systems model the translation process using pairs of corresponding sequences of words extracted from parallel corpora. These biphrases are stored in phrase tables that typically contain several millions such entries, making it difficult to assess their quality without going to the end of the translation process. Our work is based on the examplifying study of phrase tables generated from the Europarl data, from French to English. We give some statistical information about the biphrases contained in the phrase table, evaluate the coverage of previously unseen sentences and analyse the effects of pruning on the translation.
Source: Työväentutkimus Vuosikirja
Author: Galbrun, Esther
Institution: University of Helsinki
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2136933870