[PDF] Top 20 The RWTH Aachen Machine Translation System for WMT 2010

... each system as well as other sta- tistical models such as a special trigram language ...The translation with the best total score within this lattice is selected as consensus ... See full document

... Moreover, training material was tokenized with the tool provided for the workshop and truecased, meaning that the words occuring after a strong punctuation mark were lowercased when they be- longed to a dictionary of ... See full document

... tised system shows that, in particular, the word penalty model has a very low weight (this favours short sentences) and the lexical word-based trans- lation models have a very low weight (no use of the lexical ... See full document

... the WMT 2018 unsu- pervised learning track, we combine the concepts proposed in previous research and perform a thor- ough comparison of the main components of each ... See full document

... the System Combi- nation task of the Fifth Workshop on Sta- tistical Machine Translation (WMT ...sensus translation, using additional n-best reranking techniques in two of these lan- ... See full document

... Joint Translation and Reordering (JTR) decoder is based on the implementation of the source cardinality synchronous search (SCSS) procedure described in (Zens and Ney, ...The system combines the flexibility ... See full document

... a system of similar perfor- mance as the baseline system used to generate the automatic translations, but with less than 30% of the ...both translation direc- ... See full document

... in machine translation is mainly assigned to the four groups participating in this joint ...this WMT submission was to show the quality of a joint translation by combining the knowledge of the ... See full document

... Phrase orientation model. We implemented a feature in Moses that resembles the phrase ori- entation model for hierarchical machine transla- tion as described by Huck et al. (2013). The Huck et al. (2013) ... See full document

... to System Combination (SC) for Machine Translation (MT) is a refined version of the ROVER approach in Automatic Speech Recognition (ASR) (Fiscus, 1997), with additional steps to cope with reordering ... See full document

... the WMT 2010 machine translation system combi- nation ...of system outputs then navigating the aligned out- puts from left to right where each path is a candidate ...best ... See full document

... different translation engines that are better in terms of translation quality than any of the individual hy- ...to machine translation system combination has been described by Matusov ... See full document

... the RWTH Aachen translation sys- tem as described in (Peter et ...The system was trained using the Adam optimizer (Kingma and Ba, 2014) with a learning rate of ... See full document

... a machine trans- lation ...Masselot, 2010) as well as improvements in translation quality (Green et ...from machine translation and post- editing ... See full document

... our system, but ex- tract a phrase table with only lexical ...line system, with a binary feature that enables the system to reward or penalize the application of phrases from this ... See full document

... segmentations, we apply a leave-one-out heuris- tic (Wuebker et al., 2010) during the n-best list generation step. Using these n-best lists, we it- eratively trained the phrasal and lexical feature sets, denoted ... See full document

... al., 2010) was employed. Jane has been developed at RWTH and implements the hierarchical approach as introduced by Chiang (2007) with some state-of-the-art exten- ...phrase-based translation, a ... See full document

... phrase-based translation (Chiang, 2007), a weighted synchronous context-free gram- mar is induced from parallel ...al., 2010; Huck et al., 2012c) are: phrase translation probabilities and lexical ... See full document

... smoothed 3-gram and 4-gram precisions. To that end, the training data is decoded to generate 100- best lists. We apply a leave-one-out heuristic (Wuebker et al., 2010) to make better use of the training data. ... See full document

... We also use the provided Chinese and En- glish monolingual data and apply the same pre- proceesing procedure. After the filtering, the Chi- nese and English monolingual data sets contain 27.5M and 52.9M sentences ... See full document