Papers with Moses
A Hybrid Approach for Automatic Extraction of Bilingual Multiword Expressions from Parallel Corpora (L18-1)
Copied to clipboard
| Challenge: | Specific-domain bilingual lexicons are composed of MultiWord Expressions (MWEs) the manual construction of MWEs bilingual dictionaries is costly and time-consuming. |
| Approach: | They propose to use word alignment approaches to automatically construct bilingual lexicons of MWEs from parallel corpora by formalizing the alignment process as an integer linear programming problem. |
| Outcome: | The proposed approach extracts and aligns multiword expressions from parallel corpora and then filters them using linguistic patterns to build bilingual lexicons. |
A Comparison of Two Paraphrase Models for Taxonomy Augmentation (N18-2)
Copied to clipboard
| Challenge: | a taxonomy is often used to look up concepts in text documents. |
| Approach: | They compare two state-of-the-art paraphrase models with a paraphrase dataset . they find that paraphrasing is a viable method to augment taxonomies with more terms . |
| Outcome: | The proposed model outperforms the previous model on the risk domain. |
Unsupervised Statistical Machine Translation (D18-1)
Copied to clipboard
| Challenge: | Neural Machine Translation (NMT) systems can be trained from monolingual corpora without supervision. |
| Approach: | They propose a phrase-based approach that trains from monolingual corpora . their method is based on phrase-driven Statistical Machine Translation (SMT) they propose to train NMT systems without supervision from monolinguistic corpors . |
| Outcome: | The proposed approach improves on the existing supervised systems by combining a phrase table with an n-gram language model and fine-tuning hyperparameters through an unsupervised MERT variant. |
A Large Parallel Corpus of Full-Text Scientific Articles (L18-1)
Copied to clipboard
| Challenge: | Scielo database contains articles from several research domains. |
| Approach: | They propose to build a parallel corpus from Scielo in three languages: English, Portuguese, and Spanish. |
| Outcome: | The proposed system outperforms other systems on scientific articles in English, Portuguese, and Spanish. |