A North Saami to South Saami Machine Translation Prototype

2016 ◽  
Vol 4 ◽  
pp. 11-27
Author(s):  
Lene Antonsen ◽  
Trond Trosterud ◽  
Francis M. Tyers
Keyword(s):  
Machine Translation ◽  
School Administration ◽  
Single Domain ◽  
Restricted Domain ◽  
Rule Based ◽  
Rule Based System

The paper describes a rule-based machine translation (MT) system from North to South Saami. The system is designed for a workflow where North Saami functions as pivot language in translation from Norwegian or Swedish. We envisage manual translation from Norwegian or Swedish to North Saami, and thereafter MT to South Saami. The system was aimed at a single domain, that of texts for use in school administration. We evaluated the system in terms of the quality of translations for postediting. Two out of three of the Norwegian to South Saami professional translators found the output of the system to be useful. The evaluation shows that it is possible to make a functioning rule-based system with a small transfer lexicon and a small number of rules and achieve results that are useful for a restricted domain, even if there are substantial differences b etween the languages.

scholarly journals A Rule Based Approach for Translation of Causative Construction of English and Malayalam for the Development of Prototype for Malayalam to English and English To Malayalam Bilingual Machine Translation System

2018 ◽  
Vol 7 (4.36) ◽  
pp. 542
Author(s):  
T. K. Bijimol ◽  
John T. Abraham
Keyword(s):  
Machine Translation ◽  
Translation System ◽  
Indian Languages ◽  
Rule Based ◽  
Rule Based System ◽  
Machine Translation System ◽  
Rule Based Approach ◽  
Causative Construction ◽  
Translation Systems

Malayalam is one of the Indian languages and it is a highly agglutinative and morphologically rich. These linguistic specialties of Malayalam determine the quality of all kinds of Malayalam machine translation systems. Causative sentences translations in Malayalam to English and English to Malayalam were analysed using Google Translation System and identified that causative sentence translation in these languages is not up to the mark. This paper discusses the concept and method of causative sentence handling in Malayalam to English and English to Malayalam Machine Translation Systems. A Rule-based system is proposed here to handle the causative sentence in both languages.  

Function words in statistical machine-translated Chinese and original Chinese: A study into the translationese of machine translation systems

2018 ◽  
Vol 34 (4) ◽  
pp. 752-771
Author(s):  
Chen-li Kuo
Keyword(s):  
Machine Translation ◽  
Attribute Selection ◽  
Close Attention ◽  
Function Words ◽  
Rule Based ◽  
Source Language ◽  
Statistical Mt ◽  
Chinese Texts ◽  
Translation Systems

Abstract Statistical approaches have become the mainstream in machine translation (MT), for their potential in producing less rigid and more natural translations than rule-based approaches. However, on closer examination, the uses of function words between statistical machine-translated Chinese and the original Chinese are different, and such differences may be associated with translationese as discussed in translation studies. This article examines the distribution of Chinese function words in a comparable corpus consisting of MTs and the original Chinese texts extracted from Wikipedia. An attribute selection technique is used to investigate which types of function words are significant in discriminating between statistical machine-translated Chinese and the original texts. The results show that statistical MT overuses the most frequent function words, even when alternatives exist. To improve the quality of the end product, developers of MT should pay close attention to modelling Chinese conjunctions and adverbial function words. The results also suggest that machine-translated Chinese shares some characteristics with human-translated texts, including normalization and being influenced by the source language; however, machine-translated texts do not exhibit other characteristics of translationese such as explicitation.

Learning Lessons from Bilingual Corpora: Benefits for Machine Translation

2000 ◽  
Vol 5 (2) ◽  
pp. 199-230 ◽  
Author(s):  
Oliver Streiter ◽  
Leonid L. Iomdin
Keyword(s):  
Machine Translation ◽  
Subject Domain ◽  
Rule Based ◽  
Parallel Corpora ◽  
Specific Subject ◽  
Multiword Expressions ◽  
Bilingual Corpora ◽  
Subject Domains

The research described in this paper is rooted in the endeavors to combine the advantages of corpus-based and rule-based MT approaches in order to improve the performance of MT systems—most importantly, the quality of translation. The authors review the ongoing activities in the field and present a case study, which shows how translation knowledge can be drawn from parallel corpora and compiled into the lexicon of a rule-based MT system. These data are obtained with the help of three procedures: (1) identification of hence unknown one-word translations, (2) statistical rating of the known one-word translations, and (3) extraction of new translations of multiword expressions (MWEs) followed by compilation steps which create new rules for the MT engine. As a result, the lexicon is enriched with translation equivalents attested for different subject domains, which facilitates the tuning of the MT system to a specific subject domain and improves the quality and adequacy of translation.

scholarly journals Sistem Evaluasi Jamunan Mutu Menggunakan Rule Based System Untuk Monitoring Mutu Perguruan Tinggi

2017 ◽  
Vol 7 (1) ◽  
pp. 24
Author(s):  
Sri Hartono
Keyword(s):  
Higher Education ◽  
Quality Assurance ◽  
Knowledge Base ◽  
Recommendation System ◽  
Study Program ◽  
Rule Based ◽  
Rule Based System ◽  
Quality Of Higher Education ◽  
Quality Status

The needs for continuous quality improvement resulting in the more complex. The research aims to develop system of quality assurance evaluation using rule based system to monitor the quality of higher education. This process of the research begins by documenting the daily activity of study program which consists of lecturer data, research data, service data, staff data, student data, and infrastructure data into a database. The data were evaluated by using rule based system  by adopting rules on quality standards of study program of National Accreditation Board for Higher Education as the knowledge base. Evaluation process was carried out by using the forward chaining methods by matching the existing data to the knowledge base to determine the quality status of each quality standard. While the reccomendation process was carried out by using the backward chaining methods by matching the results of quality status to the desired projection of quality status to determine the nearest target which can be achieved. The result of the research is system of quality assurance evaluation with rule based system that is capable of producing an output system in the form of internal evaluation report and recommendation system that can be used to monitor the quality of higher education. 

scholarly journals Hybrid Arabic-English Machine Translation to Solve Reordering and Ambiguity Problems

2015 ◽  
Vol 1 (4) ◽  
pp. 413
Author(s):  
Khalid Shaker Alubaidi
Keyword(s):  
Machine Translation ◽  
Target Material ◽  
Rule Based ◽  
Parallel Corpora ◽  
Linguistic Rule ◽  
Hybrid Machine Translation ◽  
In The Beginning ◽  
Better Than ◽  
Lexical Analyzer

The problem in Arabic to English rule-based machine translation is that the rule-based lexical analyzer leaves some amount of ambiguity; therefore a statistical approach is used to resolve the ambiguity problem. Rule Based Machine Translation (RBMT) uses linguistic rule between two languages which is built manually by human in general, whereas SMT uses appearance statistic of word in parallel corpora. In this paper, those different approaches are combined into Arabic-English Hybrid Machine Translation (HMT) system to get the advantage from both kind of information. In the beginning, Arabic text will be inputted into RBMT to solve reordering problem. Then, the output will be edited by SMT to solve the ambiguity problem and generate the final translation of English text. SMT is capable to do this because on the training process, it uses RBMT’s output (English) as source material and real translation (English) as target material. The results showed that the quality of translation in HMT system is better than SMT system.

scholarly journals Improving translation quality of rule-based machine translation

2002 ◽  
Author(s):  
Paisarn Charoenpornsawat ◽  
Virach Sornlertlamvanich ◽  
Thatsanee Charoenporn
Keyword(s):  
Machine Translation ◽  
Rule Based ◽  
Translation Quality

scholarly journals Comparing Rule-Based Translation to Syntax Tree Diagram Translation

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Heri Heryono
Keyword(s):  
Machine Translation ◽  
Ambiguous Sentence ◽  
Computational System ◽  
Rule Based ◽  
Morphological Process ◽  
Rule Based System ◽  
Alternative Translation ◽  
Tree Diagram ◽  
Alternative Result ◽  
Bahasa Indonesia

Machine translation has developed more effectively to be specified as modern linguistics characterization. It indicates the formalization of translating process by machine within humanly approaching. Recently, in order to help people communicate indirectly through written, machine translation has its own system to break and match the codes through comprehensive database of words pocket. In linguistics perspective, machine translation always be assisted by its definite performance through derivative computational system. The problem appears when users need to translate ambiguous sentence from English to Bahasa Indonesia or vice versa. The paper used rule-based system which contains particular parts in order to run the process of translating; starts from tokenization, pre-processing, reordering and morphological process which lead to output accuracy. And used syntactic diagram translation, which was carried out manually by generating sentences into small units. The result of this research showed that RBS runs by standard linguistics system; and the output of translating refer to basic translation without giving any alternative translation nor meaning. While using syntactic diagram, there are possibility to get alternative result not only by linguistics features but also based on signification meaning of both translations. Those techniques run by considering linguistics features in order to help users to get translation output better.

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