| Autor: |
Kotzé, Gideon, Wolff, Friedel |
| Předmět: |
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| Zdroj: |
South African Computer Journal; Dec2015, Vol. 57, p1-23, 23p |
| Abstrakt: |
We present a series of experiments involving the machine translation of Zulu to English using a well-known statistical software system. Due to morphological complexity and relative scarcity of resources, the case of Zulu is challenging. Against a selection of baseline models, we show that a relatively naive approach of dividing Zulu words into syllables leads to a surprising improvement. We further improve on this model through manual configuration changes. Our best model significantly outperforms the baseline models (BLEU measure, at p < 0.001) even when they are optimised to a similar degree, only falling short of the well-known Morfessor morphological analyser that makes use of relatively sophisticated algorithms. These experiments suggest that even a simple optimisation procedure can improve the quality of this approach to a significant degree. This is promising particularly because it improves on a mostly language independent approach--at least within the same language family. Our work also drives the point home that sub-lexical alignment for Zulu is crucial for improved translation quality. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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