• Publications
  • Influence
Statistical Phrase-Based Translation
TLDR
The empirical results suggest that the highest levels of performance can be obtained through relatively simple means: heuristic learning of phrase translations from word-based alignments and lexical weighting of phrase translation. Expand
A Systematic Comparison of Various Statistical Alignment Models
TLDR
An important result is that refined alignment models with a first-order dependence and a fertility model yield significantly better results than simple heuristic models. Expand
Minimum Error Rate Training in Statistical Machine Translation
  • F. Och
  • Computer Science
  • ACL
  • 7 July 2003
TLDR
It is shown that significantly better results can often be obtained if the final evaluation criterion is taken directly into account as part of the training procedure. Expand
Improved Statistical Alignment Models
TLDR
It is shown that models with a first-order dependence and a fertility model lead to significantly better results than the simple models IBM-1 or IBM-2, which are not able to go beyond zero-order dependencies. Expand
The Alignment Template Approach to Statistical Machine Translation
  • F. Och, H. Ney
  • Computer Science
  • Computational Linguistics
  • 1 December 2004
TLDR
A phrase-based statistical machine translation approach the alignment template approach is described, which allows for general many-to-many relations between words and is easier to extend than classical statistical machinetranslation systems. Expand
Automatic Evaluation of Machine Translation Quality Using Longest Common Subsequence and Skip-Bigram Statistics
TLDR
Two new objective automatic evaluation methods for machine translation based on longest common subsequence between a candidate translation and a set of reference translations and relaxes strict n-gram matching to skip-bigram matching are described. Expand
Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
TLDR
A framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source-channel approach as a special case and shows that a baseline statistical machinetranslation system is significantly improved using this approach. Expand
Large Language Models in Machine Translation
TLDR
Systems, methods, and computer program products for machine translation are provided for backoff score determination as a function of a backoff factor and a relative frequency of a corresponding backoff n-gram in the corpus. Expand
Improved Alignment Models for Statistical Machine Translation
TLDR
Improved alignment models for statistical machine translation are described and experimental results are presented using the Verbmobil task (German-English, 6000word vocabulary) which is a limited-domain spoken-language task. Expand
ORANGE: a Method for Evaluating Automatic Evaluation Metrics for Machine Translation
TLDR
A new evaluation method, Orange, is introduced for evaluating automatic machine translation evaluation metrics automatically without extra human involvement other than using a set of reference translations. Expand
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