Add to ORKGThis paper presents novel approaches to reordering in phrase-based statistical machine translation. We perform consistent reordering of source sentences in training and estimate a statistical translation model. Using this model, we follow a phrase-based monotonic machine translation approach, for which we develop an efficient and flexible reordering framework that allows to easily introduce different reordering constraints. In translation, we apply source sentence reordering on word level and use a reordering automaton as input
[[abstract]]In this paper, we propose a method for learning reordering model for BTG-based statistic...
In this paper, we start with the existing idea of taking reordering rules automatically derived from...
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where...
This paper presents novel approaches to reordering in phrase-based statistical ma-chine translation....
This paper surveys several state-of-the-art reordering techniques employed in Statistical Machine Tr...
In this paper, we describe a novel phrase reordering model based on predicate-argument structure. Ou...
Reordering is of essential importance for phrase based statistical machine translation (SMT). In thi...
We propose a distance phrase reordering model (DPR) for statistical machine trans-lation (SMT), wher...
We present a novel word reordering model for phrase-based statistical machine translation suited to ...
[[abstract]]We introduce a method for learning to reorder source sentences. In our approach, sentenc...
The paper presents a new method for reordering in phrase based statistical machine translation (PBMT...
Lexicalized reordering model plays a central role in phrase-based statistical machine translation sy...
We present a novel word reordering model for phrase-based statistical machine translation suited to ...
This paper describes how word alignment information makes machine translation more efficient. Follow...
We introduce a method for learning to reorder source sentences. In our approach, sentences are trans...
[[abstract]]In this paper, we propose a method for learning reordering model for BTG-based statistic...
In this paper, we start with the existing idea of taking reordering rules automatically derived from...
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where...
This paper presents novel approaches to reordering in phrase-based statistical ma-chine translation....
This paper surveys several state-of-the-art reordering techniques employed in Statistical Machine Tr...
In this paper, we describe a novel phrase reordering model based on predicate-argument structure. Ou...
Reordering is of essential importance for phrase based statistical machine translation (SMT). In thi...
We propose a distance phrase reordering model (DPR) for statistical machine trans-lation (SMT), wher...
We present a novel word reordering model for phrase-based statistical machine translation suited to ...
[[abstract]]We introduce a method for learning to reorder source sentences. In our approach, sentenc...
The paper presents a new method for reordering in phrase based statistical machine translation (PBMT...
Lexicalized reordering model plays a central role in phrase-based statistical machine translation sy...
We present a novel word reordering model for phrase-based statistical machine translation suited to ...
This paper describes how word alignment information makes machine translation more efficient. Follow...
We introduce a method for learning to reorder source sentences. In our approach, sentences are trans...
[[abstract]]In this paper, we propose a method for learning reordering model for BTG-based statistic...
In this paper, we start with the existing idea of taking reordering rules automatically derived from...
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where...