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Example-Based Statistical Machine Translation

Example-Based Statistical Machine Translation
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Statistical Machine Translation

NLP of Semitic Languages, 2014
We introduce a brief introduction to statistical machine translation for semitic languages along with an overview of machine translation approaches. We discuss the special consideration that should be taken into account when developing SMT systems for Semitic languages.
Hany Hassan, Kareem Darwish
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Statistical machine translation

2017 1st International Conference on Intelligent Systems and Information Management (ICISIM), 2017
Translation of natural language text using statistical machine translation (SMT) is a supervised machine learning problem. SMT algorithms are trained to learn how to translate by providing many translations produced by human language experts. The field SMT has gained momentum in recent three decades.
A. R. Babhulgaonkar, S. V. Bharad
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Incorporating Statistical Machine Translation Word Knowledge Into Neural Machine Translation

IEEE/ACM Transactions on Audio Speech and Language Processing, 2018
Neural machine translation (NMT) has gained more and more attention in recent years, mainly due to its simplicity yet state-of-the-art performance. However, previous research has shown that NMT suffers from several limitations: source coverage guidance ...
Xing Wang, Zhaopeng Tu, Min Zhang
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Statistical machine translation

ACM Computing Surveys, 2008
Statistical machine translation (SMT) treats the translation of natural language as a machine learning problem. By examining many samples of human-produced translation, SMT algorithms automatically learn how to translate. SMT has made tremendous strides in less than two decades, and new ideas are constantly introduced.
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Supervised OCR Error Detection and Correction Using Statistical and Neural Machine Translation Methods

Journal for Language Technology and Computational Linguistics, 2018
For indexing the content of digitized historical texts, optical character recognition (OCR) errors are a hampering problem. To explore the effectivity of new strategies for OCR post-correction, this article focuses on methods of character-based machine ...
Chantal Amrhein, S. Clematide
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Statistical Machine Translation

2009
The dream of automatic language translation is now closer thanks to recent advances in the techniques that underpin statistical machine translation. This class-tested textbook from an active researcher in the field, provides a clear and careful introduction to the latest methods and explains how to build machine translation systems for any two ...
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End-to-end statistical machine translation with zero or small parallel texts†

Natural Language Engineering, 2016
We use bilingual lexicon induction techniques, which learn translations from monolingual texts in two languages, to build an end-to-end statistical machine translation (SMT) system without the use of any bilingual sentence-aligned parallel corpora.
Ann Irvine, Chris Callison-Burch
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Statistical Machine Translation

2023
Yang Liu, Min Zhang
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