نتایج جستجو برای: mizan english persian parallel corpus
تعداد نتایج: 413519 فیلتر نتایج به سال:
In this paper we describe the development of a doctor-patient dialogue corpus to support a speech-to-speech machine translation effort for English-Persian medical dialogues. The corpus was developed by recording and transcribing English-to-English dialogues between medical students and standardized patients (actors who have been trained to portray illness or injury victims), and then translated...
In this paper, an attempt to develop a phrase-based statistical machine translation between English and Persian languages (PersianSMT) is described. Creation of the largest English-Persian parallel corpus yet presented by the use of movie subtitles is a part of this work. Two major goals are followed here: the first one is to show the main problems observed in the output of the PersianSMT syste...
PEnTrans is an automatic bidirectional English/ Persian text translator. It contains two main modules, PEnT1,2. PEnT1 translates English sentences into Persian and PEnT2 performs translation from Persian to English. WSD which is an important part in translation is done in both systems by employing a combination of extended dictionary and corpus based approaches in PEnT1 and employing a combinat...
The present research is a descriptive corpus-based translation study aiming at pinpointing the patterns of translation into Persian when dealing with English Verb Phrase Ellipsis (VPE). After scrutiny of the strategies applied by Persian translators some regular patterns were drawn, with the exception that the observed translation behavior may be taken as advantageous information for improving ...
abstract this study aimed at investigating the translation of interjections from english into persian in dubbing. to carry out this study the expressive secondary interjections found in the film four weddings and a funeral and their equivalent in persian dubbed version were analyzed through the strategies proposed by cuenca. the descriptive analysis of the corpus showed that (strategy b) i.e...
abstract: advertisements are the most accessible type of authentic materials, and this is one reason why they are used more and more in english teaching classes. for this cause, studies in the field of advertisements are very widespread nowadays. for pun is one aspect which makes advertisements more interesting, it is used more than before in advertisements. use of puns makes an advertisement m...
This paper describes the systems submitted by FBK for the MT track of IWSLT 2013. We participated in the EnglishFrench as well as the bidirectional Persian-English translation tasks. We report substantial improvements in our English-French systems over last year’s baselines, largely due to improved techniques of combining translation and language models. For our Persian-English and English-Pers...
Multilingual corpora are valuable resources for cross-language information retrieval and are available in many language pairs. However the Persian language does not have rich multilingual resources due to some of its special features and difficulties in constructing the corpora. In this study, we build a Persian-English comparable corpus from two independent news collections: BBC News in Englis...
Persian is an Indo-European language written using Arabic script, and is an official language of Iran, Afghanistan, and Tajikistan. Transliteration of Persian to English—that is, the character-bycharacter mapping of a Persian word that is not readily available in a bilingual dictionary—is an unstudied problem. In this paper we make three novel contributions. First, we present performance compar...
a bilingual corpus is considered as a very important knowledge source and an inevitable requirement for many natural language processing (nlp) applications in which two languages are involved. for some languages such as persian, lack of such resources is much more significant. several applications, including statistical and example-based machine translation needs bilingual corpora, in which lar...
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