FI:PV061 Machine Translation Intro - Course Information

PV061 Introduction to Machine Translation

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 14:00–15:50 B411

Prerequisites (in Czech)

! P061 Introduction to Machine Translation

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

• Applied Informatics (programme FI, B-AP)
• Applied Informatics (programme FI, N-AP)
• Czech Language and Literature (programme FF, M-FI) (2)
• Czech Language and Literature (programme FF, M-HS)
• Informatics with another discipline (programme FI, B-BI)
• Informatics with another discipline (programme FI, B-FY)
• Informatics with another discipline (programme FI, B-GE)
• Informatics with another discipline (programme FI, B-GK)
• Informatics with another discipline (programme FI, B-CH)
• Informatics with another discipline (programme FI, B-IO)
• Informatics with another discipline (programme FI, B-MA)
• Informatics with another discipline (programme FI, B-SO)
• Informatics with another discipline (programme FI, B-TV)
• Informatics (programme FI, B-IN)
• Informatics (programme FI, M-IN)
• Informatics (programme FI, N-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-TV)
• Upper Secondary School Teacher Training in Informatics (programme FI, N-SS)
• Health Sciences (programme LF, N-SZ, specialization Teaching Specialization Optics and Optometrics)

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.

• Enrolment Statistics (Autumn 2006, recent)
  
• Permalink: https://is.muni.cz/course/fi/autumn2006/PV061