Statistical Vs Rule Based Machine Translation; A Case Study on Indian Language Perspective
In this paper we present our work on a case study between Statistical Machien Transaltion (SMT) and Rule-Based Machine Translation (RBMT) systems on English-Indian langugae and Indian to Indian langugae perspective. Main objective of our study is to make a five way performance compariosn; such as, a...
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Main Author | |
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Format | Journal Article |
Language | English |
Published |
12.08.2017
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Subjects | |
Online Access | Get full text |
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Summary: | In this paper we present our work on a case study between Statistical Machien
Transaltion (SMT) and Rule-Based Machine Translation (RBMT) systems on
English-Indian langugae and Indian to Indian langugae perspective. Main
objective of our study is to make a five way performance compariosn; such as,
a) SMT and RBMT b) SMT on English-Indian langugae c) RBMT on English-Indian
langugae d) SMT on Indian to Indian langugae perspective e) RBMT on Indian to
Indian langugae perspective. Through a detailed analysis we describe the Rule
Based and the Statistical Machine Translation system developments and its
evaluations. Through a detailed error analysis, we point out the relative
strengths and weaknesses of both systems. The observations based on our study
are: a) SMT systems outperforms RBMT b) In the case of SMT, English to Indian
language MT systmes performs better than Indian to English langugae MT systems
c) In the case of RBMT, English to Indian langugae MT systems perofrms better
than Indian to Englsih Language MT systems d) SMT systems performs better for
Indian to Indian language MT systems compared to RBMT. Effectively, we shall
see that even with a small amount of training corpus a statistical machine
translation system has many advantages for high quality domain specific machine
translation over that of a rule-based counterpart. |
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DOI: | 10.48550/arxiv.1708.04559 |