LINGUIST List 19.1387
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Thu Apr 24 2008
Diss: Comp Ling/Morphology: Mosavi Miangah: 'Morphological Analysis...'
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1. Tayebeh
Mosavi Miangah,
Morphological Analysis in the System of English-Persian
Message 1: Morphological Analysis in the System of English-Persian
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Date: 24-Apr-2008
From: Tayebeh Mosavi Miangah <mosavit hotmail.com>
Subject: Morphological Analysis in the System of English-Persian
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Institution: Russian Academy of Sciences
Program: Institute of Linguistics
Dissertation Status: Completed
Degree Date: 1992
Author: Tayebeh Mosavi Miangah
Dissertation Title: Morphological Analysis in the System of English-Persian
Linguistic Field(s):
Computational Linguistics
Morphology
Subject Language(s): English (eng)
Farsi, Western (pes)
Dissertation Director:
Yuri Nikolavich Marchuk
Dissertation Abstract:
In designing every system of machine translation one requires different kinds of information including linguistic and programming information. As far as linguistic information is concerned it is inevitable to distinguish and classify different levels of linguistic analysis which are necessary in compiling information for designing a good system of machine translation. These levels can be named as: orthographic level, phonological level, morphological level, syntactic level, semantic level and pragmatic level. Our concern in this study is the analysis of morphological level of English-Persian machine translation. The purpose of this study is to provide an appropriate procedure by which all aspects of the mentioned subject are taken into account considering applicability of the procedure to the both languages - English and Persian. For achieving this purpose, similarities as well as differences between morphological systems of the two involved languages are to be considered. Construction of general algorithm within which the problems of morphological analysis for the system of machine translation are studied stands as another aim of this work. So far as morphological analysis deals with various problems such as the problem of ambiguity and lemmatization, some new methods in these respects have been presented and discussed in detail. This research and development is useful not only for the purpose of designing machine translation, but also for a number of other applications among them formal analysis of texts for information storage and retrieval purposes, language teaching both in machine forms (Computer Aided Language Learning) and human teaching processes and the likes.
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