Paper: Hierarchical Phrase Table Combination for Machine Translation

ACL ID P13-1079
Title Hierarchical Phrase Table Combination for Machine Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013

Typical statistical machine translation sys- tems are batch trained with a given train- ing data and their performances are large- ly influenced by the amount of data. With the growth of the available data across different domains, it is computationally demanding to perform batch training ev- ery time when new data comes. In face of the problem, we propose an efficient phrase table combination method. In par- ticular, we train a Bayesian phrasal inver- sion transduction grammars for each do- main separately. The learned phrase ta- bles are hierarchically combined as if they are drawn from a hierarchical Pitman-Yor process. The performance measured by BLEU is at least as comparable to the tra- ditional batch training method. Further- more, each phrase table is trained sepa- rately in each d...