MST-Department of English & Linguistics

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Browsing MST-Department of English & Linguistics by Author "Esther Kisilu"

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    Translation Mismatches between Google Translate and Human Translations of Sampled Kiswahili/English Newspaper Headlines
    (Kenyatta University, 2024-06) Esther Kisilu
    This study sought compare human and Google Translate (GT) translations of newspaper headlines. This comparison was with the intention of determining whether or not there were any mismatches between data translated by the human translator and GT. Both Kiswahili and English newspaper headlines were used. The mismatches identified were instrumental in classifying these errors according to their type and also ascertain the extent to which translations on Google Translate are accurate. Machine Translation (MT) is a field that has generated much interest and especially in this age of heightened technological advancement. The advent of internet and globalization has seen a spike in the demand of translation services, something that the human translator cannot possibly handle. Even so, research has proven the machine may not offer quality translations the way a human translator can because unlike the human, it may not take into consideration the context surrounding the translation as well as the cultural nuances of the source text. Both the Relevance and Skopos theories were applied. The research used both qualitative and quantitative research methodology and a descriptive research design. Simple random sampling was used to select the data to be translated while Purposive sampling was used when choosing the human translators. Fifty data sets were tested, 25 of which were in Kiswahili while 25 were in English. Content analysis was thereafter applied to interpret the translation output. The study found that there were some instances in which GT differed with the human translator. In addition, some human translations were found to slightly differ from Google translations in the wording but still had the same meaning. The study focused on the communicativeness of the translated data and found that some of the items considered exhibited meaning losses. The study identified three types of translation errors and categorized into: lexical, pragmatic and grammatical errors. The study further found that overall, GT was able to accurately convey the meaning of 31/50 (62.0%) data examined, implying that GT is 62% accurate in translating Kiswahili to English and vice versa. The study concludes that there are a number of errors related to English/Kiswahili translations and these translation errors not only change the particular meaning of Source Text (ST) but also the central purpose of the ST is not conveyed and therefore miscommunication occurs.