Machine Translation of Embedded Clauses English > French. A

Machine Translation of Embedded Clauses English > French. A Comparative Analysis
Published on Centre for Translation and Interpretation (http://translation.uonbi.ac.ke)
Machine Translation of Embedded Clauses English >
French. A Comparative Analysis of Google And Yahoo.
Babelfish Translate
Machine Translation of Embedded Clauses English > French. A
Comparative Analysis of Google And Yahoo. Babelfish Translate
Degree Programme: Master of Arts in Interpretation [1]
Student Names: Ramndani Aziz O.
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Year of Study: 2
Abstract
The main purpose of this study was to investigate whether machine translation (with specific
reference to Google Translate and Yahoo! Babelfish Translate) is able to translate embedded clauses
from English to French accurately and also to establish whether statistical machine translation (SMT)
renders a more accurate translation compared to rule-based machine translation (RBMT). The
analysis of the results led to the confirmation of the major hypothesis: machine translation cannot
translate embedded clauses accurately since almost 70% of the clauses were mistranslated by each
of the MT tools. It also established that omitting the complementizer could be a source of errors in
SMT. The study revealed too that changing the complementizer which retain the meaning in the
clause i.e.
That >which, does not affect the translation and that the fog index is not the main source of errors in
machine translation. On the overall, RBMT was found to be more accurate than SMT with its strength
lying in the syntactic aspect attributed to the grammatical rules applied in the process of translation.
It was also revealed that RBMT is more of a literal translator compared to SMT which is more of a
free translator.
Chapter one laid the groundwork of the study by anchoring it into the artificial intelligence
framework that was intertwined with statistical machine translation (SMT) and rule-based machine
translation (RBMT) paradigms. The chapter states, limits and defines the problem that has
necessitated the present research. It also establishes the objectives, hypotheses as well as the
methodological framework of the research.
Chapter two present the data (embedded clauses) that was collected form grammar books aligned
with its corresponding machine translation from Google Translate (SMT). The errors made were
analyzed at different linguistic levels i.e. lexical, semantic and syntactic as well as combination of
these errors.
Chapter three presents the same data used in chapter two that was collected from grammar books,
aligned with its corresponding machine translation from Yahoo! Babelfish Translate (RBMT). The
errors made were equally analyzed at different linguistic levels i.e. lexical, semantic and syntactic as
well as combination of these errors.
Chapter four deals with a comparative analysis of the translation results from the two paradigms. It
explains the errors made with reference to the SMT/RBMT theoretical considerations emberdded in
the major theoretical framework (artificial intelligence) in order to confirm or disconfirm the
hypotheses stated.
Finally, the last chapter summarized the whole study, detailed the findings and ended with
recommendations.
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Machine Translation of Embedded Clauses English > French. A Comparative Analysis
Published on Centre for Translation and Interpretation (http://translation.uonbi.ac.ke)
KEY WORDS: machine translation; SMT;RBMT; English>French
FULL TEXT LINK [9]
Academic Year: 2010/2011
Project Year: 2011
Project Status: completed
Project Supervisor: Dr. Helga Schroeder, Dr. Wachira A. W.
Source URL: http://translation.uonbi.ac.ke/node/870
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