The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Quality Assurance in Computer-Assisted Translation in Business Environments
|
|
Author(s): Sanja Seljan (Faculty of Humanities and Social Sciences, University of Zagreb, Croatia), Nikolina Škof Erdelja (Ciklopea, Croatia), Vlasta Kučiš (Faculty of Arts, University of Maribor, Slovenia), Ivan Dunđer (Faculty of Humanities and Social Sciences, University of Zagreb, Croatia)and Mirjana Pejić Bach (Faculty of Economics and Business, University of Zagreb, Croatia)
Copyright: 2021
Pages: 24
Source title:
Natural Language Processing for Global and Local Business
Source Author(s)/Editor(s): Fatih Pinarbasi (Istanbul Medipol University, Turkey)and M. Nurdan Taskiran (Istanbul Medipol University, Turkey)
DOI: 10.4018/978-1-7998-4240-8.ch011
Purchase
|
Abstract
Increased use of computer-assisted translation (CAT) technology in business settings with augmented amounts of tasks, collaborative work, and short deadlines give rise to errors and the need for quality assurance (QA). The research has three operational aims: 1) methodological framework for QA analysis, 2) comparative evaluation of four QA tools, 3) to justify introduction of QA into CAT process. The research includes building of translation memory, terminology extraction, and creation of terminology base. Error categorization is conducted by multidimensional quality (MQM) framework. The level of mistake is calculated considering detected, false, and not detected errors. Weights are assigned to errors (minor, major, or critical), penalties are calculated, and quality estimation for translation memory is given. Results show that process is prone to errors due to differences in error detection, harmonization, and error counting. Data analysis of detected errors leads to further data-driven decisions related to the quality of output results and improved efficacy of translation business process.
Related Content
|
Wasswa Shafik.
© 2024.
25 pages.
|
|
Muthmainnah Muthmainnah, Eka Apriani, Prodhan Mahbub Ibna Seraj, Ahmed J. Obaid, Ahmad M. Al Yakin.
© 2024.
17 pages.
|
|
Arkar Htet, Sui Reng Liana, Theingi Aung, Amiya Bhaumik.
© 2024.
26 pages.
|
|
Shwetha Baliga, Harshith K. Murthy, Apoorv Sadhale, Dhruti Upadhyaya.
© 2024.
18 pages.
|
|
Manoj Kumar Pandey, Jyoti Upadhyay.
© 2024.
21 pages.
|
|
R. Angeline, S. Aarthi, Rishabh Jain, Muzamil Faisal, Abishek Venkatesan, R. Regin.
© 2024.
16 pages.
|
|
Gagan Deep, Jyoti Verma.
© 2024.
20 pages.
|
|
|