 Workshop
Programme |
LDP-teaching is not included in the Undergraduate Studies Programme,
but it is included in the new Postgraduate Studies Programme at Ionian
University. (Postgraduate Studies at Ionian University are starting
this month). The course will be taught during the second semester and it
is entitled "Theory and Applications of machine Translation".
Theory and Applications of machine Translation
This course is scheduled for 20 hours and it is designed to:
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develop awareness and sensitise students with regards to how the computer
and the translation process are related (the theory, the laboratory prototypes
and the commercial potential of this technology)
-
introduce students to basic concepts and principles of Machine Translation
and NLP in the scope of the broader sense of Language Technology
-
present and explain the role of linguistics and computer science in MT
and NLP
-
present the history and future prospects of using computers in relation
to natural language
The overall aim of the course is that students who finish the course will
have a good understanding of how MT is defined, the technologies involved,
the current situation, and the future outlook. It is hoped that this will
provide them with a strong foundation for further experience in MT either
at the level of further studies, or at the level of introducing the MT
practice in their future work.
Machine Translation Course Syllabus
1. Introduction
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Definition
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Historical Overview
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Relation of Computer Science and Linguistics (NLP, LE, Computational Linguistics,
etc.)
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Descriptive vs. Procedural Representations
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Areas of Application: MT, Q/A systems, Text Understanding and Generation,
CALL, Speech Processing, etc.
2. System Architecture
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Types of MT (FAHQMT, MAHT, HAMT, Pre-Editing,
Post-Editing, Interactive ??)
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Early Systems (TAUM, METEO, SYSTRAN,GETA,LOGOS,etc.)
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Transfer-based MT
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Interlingua-based MT
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Multi/bi -lingual MT
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1st vs 2nd generation systems
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State-of-the-art MT: EBMT, KBMT, TM, Statistical MT, MT and the Internet
3. System Design
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Linguistic vs Computational Data
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Robustness (????????/????????????)
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Correcting,Updating
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Upgrading
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Data Structures (Language and Computational)
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Modularity
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Parameters of time,space,performance
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System evaluation: basic principles
4. Linguistic Data Processing for MT
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Parsers
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Dictionaries
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Grammars
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Other tools (segmentors, taggers, corpora, etc.)
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Chomsky Hierarchy
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FSAs, ATNs, Context-free grammars, Context-Sensitive grammars
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Unification
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Formalisms:
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Unification,
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TFS
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etc.
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Overview of Contemporary Grammar Theory:Xbar, UG,LFG, GPSG, CG, HPSG
5. Linguistic Issues in MT
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Ambiguity
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Grammatical phenomena at all language levels
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Greek grammar representation in existing systems
6. Review of MT situation
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Review of basic MT terms
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The situation today:NLP, Language Engineering, the role of the European
Commission, etc.
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Re-defining MT, NLP, Language Technology in the face of the Information
Age.
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