Abstract
The study reported in this paper considered English to Yoruba machine translation system for prepositional phrase. The prepositional phrase machine translation system is a subset of English to Yoruba machine translation (EYMT) system. There are issues to address in English to Yoruba machine translation system. Some of these issues are: serial verb, split verbs, noun phrase, verb phrase, numerals and prepositional phrase to mention few. The prepositional phrase (PP) plays a significant role in EYMT system because it describes the object position in a sentence. The two languages are subject verb object (SVO). In some sentences PP can be in subject and object positions. The object position was considered in the study reported in this paper. The theoretical framework was considered first. Therein the structure of PP was x-rayed and the translation process was modelled and designed. The UML was used to design the system. The flowchart, sequence, use case, and class diagrams were designed using the UML. A bilingual database (lexicon) was built to store words from the source language (English) and its equivalent target language (Yoruba), and the system translation process model was implemented using the Java programming language. The developed system was tested and the sample outputs were compared with the Yoruba Google translator outputs. The system performed better than the Yoruba Google translator in terms of good orthography and syntax.
Highlights
Yorùbá language is spoken by over 40 million people within and outside Nigeria [1]
Significant differences relating to the performance of both males and females were recorded where females scored higher marks than the males. These findings suggested that acquired skills and abilities involved in translation appeared to be more strongly activated in the English-Arabic tasks in women as compared to the men
This is derived from the whole sentence, the prepositional phrase (PP) re-write rules were designed for the two languages
Summary
Yorùbá language is spoken by over 40 million people within and outside Nigeria [1]. The Yorùbá language is spoken in Africa, Brazil, Cuba and other parts of the world. “Ref [5]” proposes a phrase-based Statistical Machine Translation (SMT) system that translates English sentences to Bangla. “Ref [8]” did research on split verbs as one of the issues of English to Yorùbá machine translation system. “Ref [9]” proposes the alternatives for the use of He/she/it => Ó of the third personal plural of English to Yorùbá machine translation system. “Ref [10]” proposes a rule-based approach for English to Yorùbá Machine Translation System. “Ref [12]” propose web-based English to Yorùbá machine translation system. “Ref [13]” considers a hybrid approach to English to Yorùbá machine translation. “Ref [14]” propose English to Yorùbá machine translation system for noun phrase. It was evaluated using Nigerian daily news and the system translation accuracy using some phrases was 90 percent
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