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Hybrid Machine Translation Approaches for Low-Resource Languages / Hybrid Machine Translation Approaches for Low-Resource LanguagesKamran, Amir January 2011 (has links)
In recent years, corpus based machine translation systems produce significant results for a number of language pairs. However, for low-resource languages like Urdu the purely statistical or purely example based methods are not performing well. On the other hand, the rule-based approaches require a huge amount of time and resources for the development of rules, which makes it difficult in most scenarios. Hybrid machine translation systems might be one of the solutions to overcome these problems, where we can combine the best of different approaches to achieve quality translation. The goal of the thesis is to explore different combinations of approaches and to evaluate their performance over the standard corpus based methods currently in use. This includes: 1. Use of syntax-based and dependency-based reordering rules with Statistical Machine Translation. 2. Automatic extraction of lexical and syntactic rules using statistical methods to facilitate the Transfer-Based Machine Translation. The novel element in the proposed work is to develop an algorithm to learn automatic reordering rules for English-to-Urdu statistical machine translation. Moreover, this approach can be extended to learn lexical and syntactic rules to build a rule-based machine translation system.
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Online Machine Translator System and Result ComparisonSyahrina, Alvi January 2011 (has links)
Translation from one human language to another has been using the help of the capabilities of computer advances. There are a lot of machine translators nowadays, each adapts to different machine translator approaches. This thesis presents the distinction between two selected machine translator approaches, statistical machine translator (SMT) and hybrid machine translator (HMT). The research focuses on creating evaluation for two machine translator of different approaches by both textual studies and evaluation experiment. The result of this research is an evaluation of the translator system and also the translation result. This result is then hoped to add information into the history of machine translators. / Program: Kandidatutbildning i informatik
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