[PDF] Top 20 Triplet Lexicon Models for Statistical Machine Translation

... Table 3 shows the effect of a maximum distance constraint for the Spanish-English direction. Due to the large amount of triplets (we extract roughly two billion triplets 2 for the EPPS data), we drop all triplets that ... See full document

... In this work, a slightly different procedure was used that operates directly on the translation lat- tices. We believe that this is more efficient than reranking n-best lists since it guarantees that al- ways all ... See full document

... We carry out an experimental evaluation to inves- tigate the potential of the deep syntax language model we describe in this paper independently of any machine translation system. We train a 5- gram deep ... See full document

... For this work we use the ORLM. The crux of the ORLM is an online perfect hash function that pro- vides the ability to insert and delete from the data structure. Consequently the ORLM has the abil- ity to adapt to an ... See full document

... In our initial experiments, we trained a neural network to estimate the forward phrase transla- tion probability P ( ¯ t | ¯ s ) . The maximal phrase length was set to seven words, as it is also used during the standard ... See full document

... BLE can be used to address the accuracy problem of SMT, which estimates comparable features for the translation pairs in the translation model (Klemen- tiev et al., 2012). BLE also can be used to address ... See full document

... the translation and language models can further improve the translation ...a translation model trained on a concatenation of S → T and T → S parallel corpora and a language model compiled from ... See full document

... To set up our systems, we employ the open source statistical machine translation toolkit Jane (Vilar et al., 2010; Vilar et al., 2012), which is freely avail- able for non-commercial use. Jane ... See full document

... standard models used in statistical machine transla- tion (SMT), which are usually conditioned on word identities rather than word ...channel models in both directions, simple count ... See full document

... Finally, we comment on differences between our Arabic-English results and the well-known high dis- tortion system of Zollmann et al. (2008), who find optimal baseline performance at a distortion limit of 9. First, they ... See full document

... these models yield improve- ments in alignment and translation performance on Arabic-English and Chinese-English tasks, and that the reordering model can be integrated into large evaluation ... See full document

... that models sentence genera- tion ...use models whose score can be computed ...language models define sentence generation hierarchically (Shen et ... See full document

... the machine translation system was the direct textual output from an automatic speech recognition (ASR) decoder that was a component of a speech- to-speech translation ...the translation ... See full document

... Often more data is better data, and so it should come as no surprise that recently statistical machine trans- lation (SMT) systems have been improved by the use of large language models (LM). ... See full document

... best translation practice differs widely across genres, topics, and di- alects, and even depends on a particular author’s or publication’s style; the word “domain” is often used to indicate a particular ... See full document

... word reorderings during the translation process. Trying all possible word reordering is an NP-Complete prob- lem as shown in (Knight, 1999), which makes search- ing for the optimal solution among all possible ... See full document

... the translation models trained on material chronologically closer to the given test ...the models that are retrained show that we achieve a higher translation performance when using more up- ... See full document

... Statistical machine translation (SMT) systems re- quire large parallel corpora in order to be able to obtain a reasonable translation ... See full document

... GEC models. The performance of four recent models, namely three neural machine translation (NMT)- based models (LSTM, CNN, and transformer) and a statistical machine ... See full document

... the models and include some semantic and syntactic infor- mation ...another statistical train- ing procedure (Och, 1999) which often pro- duces word classes including words with the same semantic meaning in ... See full document