earticle

영어

This study aims to explore the limitations of Neural Machine Translation (NMT) in processing spoken text. Following literature review, an analysis of government press briefing transcriptions that have been processed by Google Translate will be analyzed based on the framework of the features of spoken language. The concept of cognitive complements will be employed to attempt to explain any identified pattern of errors made by the NMT. Specifically, the role of cognitive complements that exist outside of the utterances will be discussed, drawing on the theories of Lederer(1989) and Gutt(2000) among other scholars. A sample text analysis of spoken text translation will be conducted to investigate whether this inherently human mechanism works in the latest neural based machine translation engine, ‘Google Translate’. Analysis will show that while Google Translate demonstrated quite impressively on some of the well-crafted segments that resemble written language, it performed poorly on segments laden with features of spoken language. The findings of the study suggest that the need for human interpreters’ in mediating highly professional inter-lingual communication will likely persist in the future. As long as artificial intelligence does not acquire the ability to infer meaning from the cognitive complements as human beings to, the application of automated inter-lingual interpreting devices may need to be limited to certain market segments such as for tourism, entertainment and socializing. leisure.