Unawareness of Common Errors in English and Its Impact on Human vs. Machine Translation Into Arabic
Bibliographic Data
| ID | 21806850 |
|---|---|
| Authors | Yasir Younis Al-Badrany (0000-0002-4075-3010, University of Mosul, corresponding author) |
| Year | 2022 |
| Volume | 13 |
| Issue | 1 |
| Pages | 145-160 |
| Publication date | 2022-12-31 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Theory and Practice in Language Studies (JOURNAL) |
| Journal identifiers | ISSN: 1799-2591 • E-ISSN: 2053-0692 |
| Publisher | Academy Publication (PUBLISHER • GB) |
| DOI | 10.17507/tpls.1301.17 |
| OpenAlex | W4313476531 |
| Language | EN |
| References cited | 1 |
This study investigates the rate of unawareness of common errors in English and its impact on human vs. machine translation into Arabic. It analyzes the reaction of human and machine translators when encountering English sentences with common errors, and its impact on translation process. Translators are readers in the first place, they have to comprehend what they read in the SL in order to convey it in the TL. In order for the ST message to be correctly conveyed into the TL, detecting errors and correcting them before translating is a necessity. The study is conducted through presenting 40 SL texts and evaluating their 680 TL texts translated by 14 MA students of translation and 3 online machine translators. Results show that the rate of unawareness of common errors is 51% for human translators and 79% for machine translators
Arabic · Evaluation of machine translation · Example-based machine translation · Linguistics · Machine translation · Machine translation software usability · Natural language processing · Programming language · Speech recognition · Word error rate · Computer Science · Natural Language Processing Techniques · Philosophy · Artificial Intelligence
| Highly cited | No |
|---|