Year: 2009
Type: conference-paper
Abstract: We investigate the impact of the original source language (SL) on French–English PB-SMT. We train four configurations of a state-of-the-art PB-SMT system based on French–English parallel corpora which differ in terms of the original SL, and conduct experiments in both translation directions. We see that data containing original French and English translated from French is optimal when building a system translating from French into English. Conversely, using data comprising exclusively French and English translated from several other languages is suboptimal regardless of the translation direction. Accordingly, the clamour for more data needs to be tempered somewhat; unless the quality of such data is controlled, more training data can cause translation performance to decrease drastically, by up to 38% relative BLEU in our experiments.
Authors: Sylwia Ozdowska, Andy Way
Institution: Dublin City University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Science Foundation Ireland
OpenAlex ID: W2111568449