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Considerations in maximum mutual information and minimum classification error training for statistical machine translation

Authors: nan

Publication: TIPSTER (2005)

DOI: nan

. Discriminative training methods are used in statistical machine translation to ef- fectively introduce and combine additional knowledge sources within the translation proc- ess. Although these methods are described in …...

3462

The RWTH Phrase-based Statistical Machine Translation System

Authors: nan

Publication: TIPSTER (2005)

DOI: nan

We give an overview of the RWTH phrase-based statistical machine translation system that was used in the evaluation campaign of the International Workshop on Spoken Lan- guage Translation 2005. We …...

20461

A Large Scale Distributed Syntactic, Semantic and Lexical Language Model for Machine Translation

Authors: nan

Publication: TIPSTER (2011)

DOI: nan

This paper presents an attempt at building a large scale distributed composite language model that simultaneously accounts for local word lexical information, mid-range sentence syntactic structure, and long-span document semantic …...

36453

Oracle-based Training for Phrase-based Statistical Machine Translation

Authors: nan

Publication: TIPSTER (2011)

DOI: nan

A Statistical Machine Translation (SMT) system generates an n-best list of candidate translations for each sentence. A model er- ror occurs if the most probable translation (1-best) generated by the …...

3328

Syntactic Parse Fusion

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

Model combination techniques have con- sistently shown state-of-the-art perfor- mance across multiple tasks, including syntactic parsing. However, they dramat- ically increase runtime and can be diffi- cult to employ in …...

34527

First the Worst: Finding Better Gender Translations During Beam Search

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractGenerating machine translations via beam search seeks the most likely output under a model. However, beam search has been shown to amplify demographic biases exhibited by a model. We aim …...

32501