Abstract
This paper proposes a new subword segmentation method for machine translation. The algorithm, which we call GenSeg, is generic in the sense that it can be applied to any language, but is designed with an emphasis on inflectional splitting, i.e. it attempts to split words on boundaries corresponding to inflectional suffixes. The main principle of the method is grouping together words that share a common middle substring, and then separating the best such substring from the rest of the word. GenSeg is a cross-language method extended with some language-specific morphological analysis rules (currently for the Latvian language). To verify its effectiveness, we performed machine translation experiments in two directions: Latvian-English and English-Latvian, obtaining minor improvements in translation quality when using our pre-processing method.
| Original language | English |
|---|---|
| Pages (from-to) | 500-509 |
| Number of pages | 10 |
| Journal | Baltic Journal of Modern Computing |
| Volume | 7 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2019 |
Keywords
- Morphological analysis
- Neural machine translation
- Word segmentation
Fingerprint
Dive into the research topics of 'Subword segmentation for machine translation based on grouping words by potential roots'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver