Abstract
Independence between sentences is an assumption deeply entrenched in the models and algorithms used for statistical machine translation (SMT), particularly in the popular dynamic programming beam search decoding algorithm. This restriction is an obstacle to research on more sophisticated discourse-level models for SMT. We propose a stochastic local search decoding method for phrase-based SMT, which permits free document-wide dependencies in the models. We explore the stability and the search parameters of this method and demonstrate that it can be successfully used to optimise a document-level semantic language model.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning |
| Publication date | 14 Jul 2012 |
| ISBN (Print) | 978-1-937284-43-5 |
| Publication status | Published - 14 Jul 2012 |
| Externally published | Yes |