A Proposed Model for Enhancing Lexical Statistical Machine Translation (ELSMT)
نویسندگان
چکیده
منابع مشابه
A Hybrid Model for Enhancing Lexical Statistical Machine Translation (SMT)
The interest in statistical machine translation systems increases currently due to political and social events in the world. A proposed Statistical Machine Translation (SMT) based model that can be used to translate a sentence from the source Language (English) to the target language (Arabic) automatically through efficiently incorporating different statistical and Natural Language Processing (...
متن کاملLexical Features for Statistical Machine Translation
Title of dissertation: LEXICAL FEATURES FOR STATISTICAL MACHINE TRANSLATION Jacob Devlin, Master of Science, 2009 Dissertation directed by: Professor Bonnie Dorr Department of Computer Science In modern phrasal and hierarchical statistical machine translation systems, two major features model translation: rule translation probabilities and lexical smoothing scores. The rule translation probabil...
متن کاملLexical Syntax for Statistical Machine Translation
Statistical Machine Translation (SMT) is by far the most dominant paradigm of Machine Translation. This can be justified by many reasons, such as accuracy, scalability, computational efficiency and fast adaptation to new languages and domains. However, current approaches of Phrase-based SMT lacks the capabilities of producing more grammatical translations and handling long-range reordering whil...
متن کاملA new model for persian multi-part words edition based on statistical machine translation
Multi-part words in English language are hyphenated and hyphen is used to separate different parts. Persian language consists of multi-part words as well. Based on Persian morphology, half-space character is needed to separate parts of multi-part words where in many cases people incorrectly use space character instead of half-space character. This common incorrectly use of space leads to some s...
متن کاملLexical Micro-adaptation in Statistical Machine Translation
We introduce a generic framework in Statistical Machine Translation (SMT) in which lexical hypotheses, in the form of a target language model local to the input sentence, are used to guide the search for the best translation, thus performing a lexical microadaptation. An instantiation of this framework is presented and evaluated on three language pairs, where these auxiliary hypotheses are deri...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: مجلة الجمعیة المصریة لنظم المعلومات وتکنولوجیا الحاسبات
سال: 2015
ISSN: 2735-4350
DOI: 10.21608/jstc.2015.119181