International Postgraduate Research Conference (IPRC)
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Item Applicability of Google Translate in Sinhalese Diglossic Contexts(International Postgraduate Research Conference 2019, Faculty of Graduate Studies, University of Kelaniya, Sri Lanka, 2019) de Silva, J.Diglossia is the co-occurrence of two different varieties of a language, for distinct functions, throughout a speech community. Sinhalese is one of the languages which depict this phenomenon, with standard written Sinhalese and spoken Sinhalese as the two varieties. Nevertheless, the necessity of employing both varieties occur in certain contexts, for example, in the translation of prose work into Sinhalese, in which narrative is generally translated into standard written Sinhalese and dialogues are translated into spoken Sinhalese, unless the necessity of foreignizing or classicizing occurs. The aim of this study has been to examine the response of Google Translate in the translation of prose work from English into Sinhalese, in which the diglossic nature of Sinhalese language should be taken into consideration. Accordingly, the study is based on Sinhalese translations of selected parts of English prose texts, produced by Google Translate. The selected parts of source texts consisted of both narratives and dialogues, and pertained to different social and cultural backgrounds. The Sinhalese translations were compared with relevant source texts and an analysis was conducted in order to determine their appropriateness. The findings of this study indicate that the diglossic nature of Sinhalese language is not given consideration in Google Translate and both written and spoken varieties are employed inconsistently in producing a translation. This inconsistently is identified to occur in both sentence level and paragraph level, with a blend of morphological and syntactic attributes of standard written Sinhalese and spoken Sinhalese. Incompatibility with diglossic languages can be adjudged a significant weakness of Google Translate, which stands parallel to the failure of producing natural output consistently. Developing the option for the user to select the required variety is identified as the measure to solve this issue.Item A Comparative Study on Technical Translation Output and Literary Translation Output of Google Translate(International Postgraduate Research Conference 2019, Faculty of Graduate Studies, University of Kelaniya, Sri Lanka, 2019) Athapattu, S.Machine Translation, with the advance of technology and the growing need for translation, has become very popular all over the world. Google Translate (GT) is an online neural machine translation service, which supports over 100 languages and has more than 200 million users daily. However, the translation quality of some texts that have been translated by GT still remains controversial. Therefore, this paper aims to identify the area Google Translate performs better, in translating literary or technical text from English to Sinhalese. Three literary texts: the poem Daffodils by William Wordsworth, an extract from Earnest Hemingway’s, Indian Camp, and an extract from Garcia Lorca’s drama House of Bernarda Alba, and three technical texts: a tender notice, an abstract and a paragraph from an informative article were selected as source texts to be translated. After these texts were translated by GT the outputs were compared with their original texts. The presentable quality of the translations was evaluated based on the faithfulness to the content and style. Further, the quality of the target language was also measured with regard to syntactic, morphological and semantic aspects. The result shows that from the translations of the given texts, the technical documents were observed to be more faithful to the original texts and of presentable quality, while the literary translations demonstrated several inaccurate outputs, thus require a considerable amount of post editing. Especially the translation of the poem has many errors since the sentence structure in poetry differs from other texts and it is written in figurative language including numerous connotations. Compared to the translation of the poem, the other two literary translations do not show a drastic difference semantically. Findings reveal that GT is more applicable for technical translations rather than literary translations which require post editingItem Quality of Machine Translation and the Role of Post-Editing(In: Proceedings of the International Postgraduate Research Conference 2017 (IPRC – 2017), Faculty of Graduate Studies, University of Kelaniya, Sri Lanka., 2017) De Silva, J.Among various extents that computer technology contributes towards translation, Machine Translation (MT) is the most convenient procedure possible, where a text can be automatically translated using a computer programme. However, despite research and experiments expanding over half a century, Machine Translation has not reached the expectations and work is still going on to make it more reliable and to make its applicability wider. The aim of this study has been evaluating the quality of machine translation output and the role of post-editing. The study was conducted taking an informative text in English as the source text, Sinhalese as the target language, and Google Translate as the Machine Translation system. A group of twenty students reading Translation Studies for their degree at the Sabaragamuwa University of Sri Lanka involved in the study. Their task was to engage in post-editing of the translation output produced by Google Translate, if required. Further, they were requested to note whether a complete Human Translation (HT) of the text is required. According to their response, the target text contained both translation and language blemishes, which need to be eluded by post-editing assigned to a translator. However, no one was of the opinion that the text needs to be retranslated by a human. A few instances had been identified where the programme had failed to grasp the underlying meaning of the source language terms. With regard to the language, errors related to spelling, concord, and word division had been identified. The response was different from student to student, suggesting that the competence level of the post-editor is also of importance. Accordingly, the conclusion is made here that post-editing has a significant role in improving the quality of Machine Translation output.