Paper: Leveraging supplemental representations for sequential transduction

ACL ID N12-1044
Title Leveraging supplemental representations for sequential transduction
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2012
Authors

Sequential transduction tasks, such as grapheme-to-phoneme conversion and ma- chine transliteration, are usually addressed by inducing models from sets of input-output pairs. Supplemental representations offer valu- able additional information, but incorporating that information is not straightforward. We apply a unified reranking approach to both grapheme-to-phoneme conversion and ma- chine transliteration demonstrating substantial accuracy improvements by utilizing heteroge- neous transliterations and transcriptions of the input word. We describe several experiments that involve a variety of supplemental data and two state-of-the-art transduction systems, yielding error rate reductions ranging from 12% to 43%. We further apply our approach to system combination, with error rate reduction...