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- Publications
- Influence
Statistical Phrase-Based Translation
- Philipp Koehn, F. Och, D. Marcu
- Computer Science
- HLT-NAACL
- 27 May 2003
We propose a new phrase-based translation model and decoding algorithm that enables us to evaluate and compare several, previously proposed phrase-based translation models. Within our framework, we… Expand
A Systematic Comparison of Various Statistical Alignment Models
We present and compare various methods for computing word alignments using statistical or heuristic models. We consider the five alignment models presented in Brown, Della Pietra, Della Pietra, and… Expand
Minimum Error Rate Training in Statistical Machine Translation
- F. Och
- Computer Science
- ACL
- 7 July 2003
Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation… Expand
Improved Statistical Alignment Models
In this paper, we present and compare various single-word based alignment models for statistical machine translation. We discuss the five IBM alignment models, the Hidden-Markov alignment model,… Expand
The Alignment Template Approach to Statistical Machine Translation
A phrase-based statistical machine translation approach the alignment template approach is described. This translation approach allows for general many-to-many relations between words. Thereby, the… Expand
Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
We present 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. All… Expand
Large Language Models in Machine Translation
This paper reports on the benefits of largescale statistical language modeling in machine translation. A distributed infrastructure is proposed which we use to train on up to 2 trillion tokens,… Expand
Automatic Evaluation of Machine Translation Quality Using Longest Common Subsequence and Skip-Bigram Statistics
- Chin-Yew Lin, F. Och
- Computer Science
- ACL
- 21 July 2004
In this paper we describe two new objective automatic evaluation methods for machine translation. The first method is based on longest common subsequence between a candidate translation and a set of… Expand
Improved Alignment Models for Statistical Machine Translation
- F. Och, C. Tillmann, H. Ney
- Computer Science
- EMNLP
- 1999
In this paper, we describe improved alignment models for statistical machine translation. The statistical translation approach uses two types of information: a translation model and a language model.… Expand
An Evaluation Tool for Machine Translation: Fast Evaluation for MT Research
In this paper we present a tool for the evaluation of translation quality. First, the typical requirements of such a tool in the framework of machine translation (MT) research are discussed. We… Expand