Statistical machine translation (SMT) is a machine translation approach where translations are generated on the basis of statistical models whose parameters are derived from the analysis of bilingual text corpora.

2024年9月4日 · Statistical Machine Translation (SMT) works by analyzing large bilingual corpora, such as parallel texts or sentence-aligned translation pairs, to identify patterns and relationships between words and phrases in different languages.

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 ...

Statistical machine translation (SMT) is a machine translation approach that uses large volumes of bilingual data to find the most probable translation for a given input. Statistical machine translation systems learn to translate by analysing the statistical relationships between original texts and their existing human translations.

2008年8月13日 · 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.

This website contains resources for research in statistical and neural machine translation, i.e. the translation of text from one human language to another by a computer that learned how to translate from vast amounts of translated text.

Statistical Machine Translation (SMT) is an approach in machine translation that learns linguistic information directly from large-scale parallel corpora, focusing on word alignments and phrases to translate natural language sentences.

It provides the necessary grounding in linguistics and probabilities, and covers the major models for machine translation: word-based, phrase-based, and tree-based, as well as machine translation evaluation, language modeling, discriminative training and advanced methods to integrate lin-guistic annotation.

2021年6月4日 · The core idea of Statistical Machine Translation (SMT) is to learn a probabilistic model from data. In the 2010s, with the advent of deep neural networks, Neural Machine Translation became a...

This chapter provides a gentle introduction to the field of statistical machine translation. We review the history of the field and highlight current applications of machine translation technology. Some pointers to available resources are also given.