A COMPARATIVE ANALYSIS OF THE PERFORMANCES OF CHATGPT, DEEPL, GOOGLE TRANSLATE AND A HUMAN TRANSLATOR IN COMMUNITY BASED SETTINGS

Authors : Özge Çetin, Ali Duran

Pages : 120-173

View : 108 | Download : 129

Publication Date : 2024-06-29

Article Type : Research Paper

Abstract :The diversity of languages is a remarkable aspect of human civilization, reflecting a wide range of cultures and life experiences. However, this diversity can sometimes pose challenges, especially during interactions with speakers of different languages. Machine translation (MT) offers a solution to minimize the impact of these linguistic barriers. MT enables swift understanding of information, effective idea exchange, and the building of relationships across varied cultural backgrounds. Prominent translation tools include Google MACHINE TRANSLATION, DeepL, Bing Microsoft Translator, and Amazon Translate. Additionally, a newer AI technology, ChatGPT by OpenAI, introduced in November 2022, has been making strides in this domain. This has sparked a debate in various industries about the potential of ChatGPT to replace human roles. A pertinent question in Translation Studies (TS) is the effectiveness of ChatGPT as a translator. It is posited that ChatGPT, akin to other machine learning models, delivers contextually richer translations. This study compares ChatGPT\'s translation capabilities with those of Google MT and DeepL across different text types, informed by past literature. To conduct this comparison, we selected text types that are traditionally challenging to translate, guided by Katharina Reiss\' Text Type Model, which categorizes texts based on their communicative purposes: informative, expressive, and operative. This study assesses the translations of source texts on education, heathcare and law by ChatGBT, DeepL, Google MT, and a human translator, drawing certain conclusions in consideration of these categories. Our research adopts a qualitative approach, evaluating the translations using a machine translation quality model, called the Multidimensional Quality Metrics (MQM) model. The insights from this study will benefit T&I researchers interested in machine translation and the users of these technologies.Keywords: ChatGPT, DeepL, Google Translate, Artificial Intelligence, Machine Translation, Translation Quality
Keywords : ChatGPT, DeepL, Google Translate, Yapay Zekâ, Makine Çevirisi, Çeviri Kalitesi, İnsan Çevirisi