Development of an automatic news summarizer for isiXhosa language

Master's Thesis from the year 2017 in the subject Speech Science / Linguistics, grade: 75, , course: Computer Science, language: English, abstract: From practice perspective, given the abundance of digital content nowadays, coming up with a technological solution that summarizes written text without losing its message, coherence and cohesion of ideas is highly essential. The technology saves time for readers as well as gives them a chance to focus on the contents that matter most. This is one of the research areas in natural language processing/ information retrieval, which the dissertation tries to contribute to. It tries to contextualize tools and technologies that are developed for other languages to automatically summarize textual Xhosa news articles. Specifically, the dissertation aims at developing a text summarizer for textual Xhosa news articles based on the extraction methods. In doing so, it examines the literature and understands the techniques and technologies used to analyze contents of a written text, transform and synthesize it, the phonology and morphology of the Xhosa language, and finally, designs, implements and test an extraction-based automatic news article for the Xhosa language. Given comprehension and relevance of the literature review, the research design, the methods and tools and technologies used to design, implement and test the pilot system. Two approaches were used to extract relevant sentences, which are, term frequency and sentence position. The Xhosa summarizer is evaluated using a test set. This study has employed both subjective and objective evaluation methods. The results of both methods are satisfactory. Keywords: Xhosa, Automatic Text Summarization, Term Frequency and Sentence Position.