scholarly journals Arabic to English Machine Translation of Verb Phrases Using Rule-Based Approach

2012 ◽  
Vol 8 (3) ◽  
pp. 277-286
Author(s):  
S.
Keyword(s):  
Machine Translation ◽  
Rule Based ◽  
Verb Phrases ◽  
Rule Based Approach

Classical Arabic English Machine Translation Using Rule-based Approach

2012 ◽  
Vol 13 (1) ◽  
pp. 79-86
Author(s):  
Huda Alhusain Hebresha ◽  
Mohd Juzaiddin Ab Aziz
Keyword(s):  
Machine Translation ◽  
Rule Based ◽  
Rule Based Approach ◽  
Classical Arabic

Rule Based and Expectation Maximization algorithm for Arabic-English Hybrid Machine Translation

2016 ◽  
Vol 5 (2) ◽  
pp. 72
Author(s):  
Arwa Hatem Alqudsi ◽  
Nazlia Omar ◽  
Rabha W. Ibrahim
Keyword(s):  
Em Algorithm ◽  
Machine Translation ◽  
Expectation Maximization ◽  
Statistical Machine Translation ◽  
Expectation Maximization Algorithm ◽  
Algorithm Performance ◽  
Rule Based ◽  
Hybrid Machine ◽  
Hybrid Machine Translation ◽  
Rule Based Approach

<p><strong> </strong>It is practically impossible for pure machine translation approach to process all of translation problems; however, Rule Based Machine Translation and Statistical Machine translation (RBMT and SMT) use different architectures for performing translation task. Lexical analyser and syntactic analyser are solved by Rule Based and some amount of ambiguity is left to be solved by Expectation–Maximization (EM) algorithm, which is an iterative statistic algorithm for finding maximum likelihood. In this paper we have proposed an integrated Hybrid Machine Translation (HMT) system. The goal is to combine the best properties of each approach. Initially, Arabic text is keyed into RBMT; then the output will be edited by EM algorithm to generate the final translation of English text. As we have seen in previous works, the performance and enhancement of EM algorithm, the key of EM algorithm performance is the ability to accurately transform a frequency from one language to another. Results showing that, as proved by BLEU system, the proposed method can substantially outperform standard Rule Based approach and EM algorithm in terms of frequency and accuracy. The results of this study have been showed that the score of HMT system is higher than SMT system in all cases. When combining two approaches, HMT outperformed SMT in Bleu score.</p>

Translational Mismatches Involving Clitics (Illustrated from Serbian ~ Catalan Language Pair)

2015 ◽  
pp. 235-255
Author(s):  
Jasmina Milićević ◽  
Àngels Catena
Keyword(s):  
Machine Translation ◽  
Phrase Structure ◽  
Linguistic Theory ◽  
Target Language ◽  
Clitic Doubling ◽  
Rule Based ◽  
Linguistic Representations ◽  
Rule Based Approach ◽  
Translation Systems ◽  
Language Pair

Translation of sentences featuring clitics often poses a problem to machine translation systems. In this chapter, we illustrate, on the material from a Serbian ~ Catalan parallel corpus, a rule-based approach to solving translational structural mismatches between linguistic representations that underlie source- and target language sentences containing clitics. Unlike most studies in this field, which make use of phrase structure formalisms, ours has been conducted within the dependency framework of the Meaning-Text linguistic theory. We start by providing a brief description of Catalan and Serbian clitic systems, then introduce the basics of our framework to finally illustrate Serbian ~ Catalan translational mismatches involving the operations of clitic doubling, clitic climbing, and clitic possessor raising.

scholarly journals A Machine Translation System from Hindi to Sanskrit Language using Rule based Approach

2020 ◽  
Vol 21 (3) ◽  
pp. 543-554
Author(s):  
Neha Bhadwal ◽  
Prateek Agrawal ◽  
Vishu Madaan
Keyword(s):  
Machine Translation ◽  
Language Processing ◽  
Translation System ◽  
Linguistic Features ◽  
Rule Based ◽  
Pragmatic Analysis ◽  
Machine Translation System ◽  
Iot Devices ◽  
And Mathematics ◽  
Rule Based Approach

Machine Translation is an area of Natural Language Processing which can replace the laborious task of manual translation. Sanskrit language is among the ancient Indo-Aryan languages. There are numerous works of art and literature in Sanskrit. It has also been a medium for creating treatise of philosophical work as well as works on logic, astronomy and mathematics. On the other hand, Hindi is the most prominent language of India. Moreover,it is among the most widely spoken languages across the world. This paper is an effort to bridge the language barrier between Hindi and Sanskrit language such that any text in Hindi can be translated to Sanskrit. The technique used for achieving the aforesaid objective is rule-based machine translation. The salient linguistic features of the two languages are used to perform the translation. The results are produced in the form of two confusion matrices wherein a total of 50 random sentences and 100 tokens (Hindi words or phrases) were taken for system evaluation. The semantic evaluation of 100 tokens produce an accuracy of 94% while the pragmatic analysis of 50 sentences produce an accuracy of around 86%. Hence, the proposed system can be used to understand the whole translation process and can further be employed as a tool for learning as well as teaching. Further, this application can be embedded in local communication based assisting Internet of Things (IoT) devices like Alexa or Google Assistant.

scholarly journals Various Approaches of Machine Translation for Marathi to English Language

2021 ◽  
Vol 40 ◽  
pp. 03026
Author(s):  
Nilesh Shirsath ◽  
Aniruddha Velankar ◽  
Ranjeet Patil ◽  
Shilpa Shinde
Keyword(s):  
Natural Language ◽  
Machine Translation ◽  
English Language ◽  
Human Intervention ◽  
Rule Based ◽  
Neural Machine Translation ◽  
Comprehensive Review ◽  
Generic Term ◽  
Rule Based Approach

Machine Translation (MT) is a generic term for computerised systems that generate translations from one natural language to another, with or without human intervention. Text may be used to examine knowledge, and turning that information into pictures helps people to communicate and acquire information.There seems to be a lot of work conducted on translating English to Hindi, Tamil, Bangla and other languages. The important parts of translation are to provide translated sentences with correct words and proper grammar. There has been a comprehensive review of 10 primary publications used in research. Two separate approaches are proposed, one uses rule based approach and other uses neural-machine translation approach to translate basic Marathi phrases to English. While designed primarily for Marathi-English language pairs, the design can be applied to other language pairs with a similar structure.

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