n South African Computer Journal - Syllabification and parameter optimisation in Zulu to English machine translation : research article
|Article Title||Syllabification and parameter optimisation in Zulu to English machine translation : research article|
|© Publisher:||South African Computer Society (SAICSIT)|
|Journal||South African Computer Journal|
|Affiliations||1 University of South Africa and 2 University of South Africa|
|Publication Date||Dec 2015|
|Pages||1 - 23|
|Keyword(s)||Alignment, English, Machine translation, Word segmentation and Zulu|
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.
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