Abstract
The field of natural language processing enables machines to read and understand the languages human being speaks. There are three major languages in Nigeria: YorÌ€ubá, Igbo and Hausa. YorÌ€ubá, a major Nigeria language spoken by over fifty million people which has the potentials of serving as medium for scientific and technological development deserves more recognition than it is in Nigeria today. Developing a computational model for English language and Yoruba language noun-phrases involve a profound understanding of the syntactic and grammatical features of the two languages as well as their vocabularies since they are not related syntactically and grammatically. Twenty nine rules were formulated for the noun phrase translations which were specified using the context free grammar (CFG). We then modeled and recognized the grammar of the language using the finite state automata (FSA) whose operations was based on the first set techniques. The first sets techniques allow the parser to choose which production rule to apply based on the first input word of an input phrase. We also developed a bilingual lexicon which is made up of words in English language with their corresponding Yoruba counterparts and their equivalent part of speech. The model was implemented using PHP Hypertext Preprocessor (PhP) programming language and my structured query language (SQL) and was tested on four-hundred randomly selected noun-phrases and gives accuracy of 91% which is quite encouraging.
Key words: Natural language processing, English, Yoruba, computational model, noun-phrases, translation system, context-free grammar and finite state automata.
