DeepAI AI Chat
Log In Sign Up

A case study on English-Malayalam Machine Translation

by   Sreelekha S, et al.

In this paper we present our work on a case study on Statistical Machine Translation (SMT) and Rule based machine translation (RBMT) for translation from English to Malayalam and Malayalam to English. One of the motivations of our study is to make a three way performance comparison, such as, a) SMT and RBMT b) English to Malayalam SMT and Malayalam to English SMT c) English to Malayalam RBMT and Malayalam to English RBMT. We describe the development of English to Malayalam and Malayalam to English baseline phrase based SMT system and the evaluation of its performance compared against the RBMT system. Based on our study the observations are: a) SMT systems outperform RBMT systems, b) In the case of SMT, English - Malayalam systems perform better than that of Malayalam - English systems, c) In the case RBMT, Malayalam to English systems are performing better than English to Malayalam systems. Based on our evaluations and detailed error analysis, we describe the requirements of incorporating morphological processing into the SMT to improve the accuracy of translation.


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 Ma...

Does Syntactic Knowledge help English-Hindi SMT?

In this paper we explore various parameter settings of the state-of-art ...

English-Bhojpuri SMT System: Insights from the Karaka Model

This thesis has been divided into six chapters namely: Introduction, Kar...

Story Generation from Sequence of Independent Short Descriptions

Existing Natural Language Generation (NLG) systems are weak AI systems a...

Comparison of SMT and RBMT; The Requirement of Hybridization for Marathi-Hindi MT

We present in this paper our work on comparison between Statistical Mach...

Neural versus Phrase-Based Machine Translation Quality: a Case Study

Within the field of Statistical Machine Translation (SMT), the neural ap...

Translating the Unseen? Yorùbá → English MT in Low-Resource, Morphologically-Unmarked Settings

Translating between languages where certain features are marked morpholo...