Phrase-Based Translation Models
نویسنده
چکیده
In previous lectures we’ve seen IBM translation models 1 and 2. In this note we will describe phrasebased translation models. Phrase-based translation models give much improved translations over the IBM models, and give state-of-the-art translations for many pairs of languages. Crucially, phrase-based translation models allow lexical entries with more than one word on either the source-language or target-language side: for example, we might have a lexical entry (le chien, the dog) specifying that the string le chien in French can be translated as the dog in English. The option of having multi-word expressions on either the source or target-language side is a significant departure from IBM models 1 and 2, which are essentially word-to-word translation models (i.e., they assume that each French word is generated from a single English word). Multi-word expressions are extremely useful in translation; this is the main reason for the improvements that phrase-based translation models give. More formally, a phrase-based lexicon is defined as follows:
منابع مشابه
Statistical Translation Models: A Literature Survey
In this survey, we briefly study Phrase-based, Factored and Hierarchical translation models. First we learn basics of Phrase-based model. Then we get introduced to an interesting SMT approach called Factored translation models. We also study mathematical modeling of the Factored models. Finally, we compare Factored models with Phrase-based models and know their disadvantages which are pulling t...
متن کاملEntropy-based Pruning for Phrase-based Machine Translation
Phrase-based machine translation models have shown to yield better translations than Word-based models, since phrase pairs encode the contextual information that is needed for a more accurate translation. However, many phrase pairs do not encode any relevant context, which means that the translation event encoded in that phrase pair is led by smaller translation events that are independent from...
متن کاملExtended Translation Models in Phrase-based Decoding
We propose a novel extended translation model (ETM) to counteract some problems in phrase-based translation: The lack of translation context when using singleword phrases and uncaptured dependencies beyond phrase boundaries. The ETM operates on word-level and augments the IBM models by an additional bilingual word pair and a reordering operation. Its implementation in a phrase-based decoder int...
متن کاملA Detailed Analysis of Phrase-based and Syntax-based Machine Translation: The Search for Systematic Differences
This paper describes a range of automatic and manual comparisons of phrase-based and syntax-based statistical machine translation methods applied to English-German and English-French translation of user-generated content. The syntax-based methods underperform the phrase-based models and the relaxation of syntactic constraints to broaden translation rule coverage means that these models do not n...
متن کاملVector Space Models for Phrase-based Machine Translation
This paper investigates the application of vector space models (VSMs) to the standard phrase-based machine translation pipeline. VSMs are models based on continuous word representations embedded in a vector space. We exploit word vectors to augment the phrase table with new inferred phrase pairs. This helps reduce out-of-vocabulary (OOV) words. In addition, we present a simple way to learn bili...
متن کاملTranslation Model Based Weighting for Phrase Extraction
Domain adaptation for statistical machine translation is the task of altering general models to improve performance on the test domain. In this work, we suggest several novel weighting schemes based on translation models for adapted phrase extraction. To calculate the weights, we first phrase align the general bilingual training data, then, using domain specific translation models, the aligned ...
متن کامل