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Teaching and assessing empirical approaches to machine translation

Way, Andy orcid logoORCID: 0000-0001-5736-5930 and Gough, Nano (2003) Teaching and assessing empirical approaches to machine translation. In: MT Summit IX Workshop on Teaching Translation Technologies and Tools, 27 September 2003, New Orleans, LA, USA.

Empirical methods in Natural Language Processing (NLP) and Machine Translation (MT) have become mainstream in the research field. Accordingly, it is important that the tools and techniques in these paradigms be taught to potential future researchers and developers in University courses. While many dedicated courses on Statistical NLP can be found, there are few, if any courses on Empirical Approaches to MT. This paper presents the development and assessment of one such course as taught to final year undergraduates taking a degree in NLP.
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Institutes and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Official URL:http://www.dlsi.ua.es/t4/proceedings.html
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15319
Deposited On:18 Mar 2010 11:51 by DORAS Administrator . Last Modified 04 Dec 2018 14:59

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