Artificial intelligence is a key technology driving innovation and initiatives that impact every aspect of our lives. This technology is particularly used in machine learning, expert systems, natural language processing, speech systems, improvement processes, vision systems, and robotic systems. Technological innovations and developments such as communication and information sharing have expanded the translation market. Consequently, the demand for translation has increased. Changes and developments in market needs have led to the advancement of machine translation software. In recent years, Neural Machine Translation (NMT) based on Artificial Intelligence has been developed for this purpose. In NMT, artificial intelligence and neural networks are used to better reveal the meaning of a sentence and the differences between them. However, at the end of the AI-based Machine Translation process, the quality of the translation product still needs to be monitored and controlled. In cases where artificial intelligence falls short, the translation product is verified by the final editing done by an expert translator. Systran and Ted have partnered to create AI-based neural translation models and establish a translation infrastructure that will enable more quality translation. This partnership aims to further advance machine learning based on artificial intelligence in the field of translation. In this study, the innovative reflections of artificial intelligence in the field of translation were discussed in a technological context. As it strengthens with software and compilation bases, it can be predicted that the AI-based translation product will be realized with fewer errors.
Birincil Dil | İngilizce |
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Konular | Dünya Dilleri, Edebiyatı ve Kültürü (Diğer) |
Bölüm | Makaleler |
Yazarlar | |
Erken Görünüm Tarihi | 19 Aralık 2023 |
Yayımlanma Tarihi | 28 Aralık 2023 |
Gönderilme Tarihi | 16 Kasım 2023 |
Kabul Tarihi | 18 Aralık 2023 |
Yayımlandığı Sayı | Yıl 2023 Cilt: 10 Sayı: 3 |
TURKOPHONE | 2014 | ISSN: 2148-6808
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.