PV061 Introduction to Machine Translation

Faculty of Informatics
Autumn 2007
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
Teacher(s)
prof. PhDr. Karel Pala, CSc. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: prof. PhDr. Karel Pala, CSc.
Timetable
Thu 12:00–13:50 B204
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course offers the information about the basics of machine translation. Main machine translation techniques and systems are discussed. The attention is also payed to the ambiguity problem, relations to the knowledge representation and semantic representation.
Syllabus
  • Machine Translation (MT) and its Relation to AI
  • History of MT and the state of art.
  • Approaches to MT: binary MT, interlingua based MT, techniques using parallel corpora.
  • Translation process: lexical analysis and lexicons, morphological and syntactic analysis and representation of sentence structure, transfer, problems of meaning representation, synthesis.
  • Key issues of MT: ambiguity problem, knowledge representation, semantic issues, terminology.
  • Some successful MT systems: TAUM-METEO, TAUM-AVIATIC, EUROTRA, the existing systems working with Czech language - short overview: TRANSEN, PC-TRANSLATOR.
  • EU framework: project like GENELEX, EAGLES, standardization, multipurpose and reusable resources within EC.
  • Examples and experiments: small experimental translation system in Prolog - Czech - English.
Literature
  • HUTCHINS, W. John and Harold L. SOMERS. An introduction to machine translation. London: Academic Press, 1992, xxi, 362 s. ISBN 0-12-362830-X. info
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2015, Autumn 2017, Autumn 2019, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2007, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2007/PV061