Development of english to yoruba machine translator, using syntax-based model (2020)
Machine translators are required to produce the best possible translation without human assistance. Every machine translator requires programs, automated dictionaries, and grammars to support translation. Studies have shown that the fluency of machine translators depends on the approach or model adopted for their respective developments. Machine translators do not simply involve substituting words in one language for another, but the application of complex linguistic knowledge to decode the contextual meaning of the source text in its entirety. Approaches to machine translators are divided into a single and hybrid approach. In the aim to improve on translation quality of existing English to Yoruba language translator systems, this paper adopts a syntax-based hybrid approach for translating sentences. The grammar for translation is designed and tested with Joshua (an open-source natural language toolkit). The procedure includes data collection, data preparation, data preprocessing, parsing, training of translation model, extract grammar rule, implement grammar, evaluate translations using bilingual evaluation understudy metrics. This paper discusses the translation quality of machine translators (precisely phrase-based and syntax-based) in both tabular and graphical representations. It was observed that a syntax-based translator seemly has higher translation quality than phrase-based.