A number of researchers have proposed applications of Girard’s Linear Logic [7] to computational linguistics. Most have focused primarily on the connection between linear logic and categorial grammars. In this work we show how linear logic can be used to provide an attractive encoding of phrase structure grammars for parsing structures involving unbounded dependencies. The resulting grammars ar...

In this paper, we present Neural Phrase-based Machine Translation (NPMT). Our method explicitly models the phrase structures in output sequences using SleepWAke Networks (SWAN), a recently proposed segmentation-based sequence modeling method. To mitigate the monotonic alignment requirement of SWAN, we introduce a new layer to perform (soft) local reordering of input sequences. Different from ex...

We propose to use a statistical phrasebased machine translation system in a post-editing task: the system takes as input raw machine translation output (from a commercial rule-based MT system), and produces post-edited target-language text. We report on experiments that were performed on data collected in precisely such a setting: pairs of raw MT output and their manually post-edited versions. ...

We compare two pivot strategies for phrase-based statistical machine translation (SMT), namely phrase translation and sentence translation. The phrase translation strategy means that we directly construct a phrase translation table (phrase-table) of the source and target language pair from two phrase-tables; one constructed from the source language and English and one constructed from English a...

Wedescribe Phrasal Rank-Encoding (PR-Enc), a novel method for the compression of wordaligned target language data in phrase tables as used in phrase-based SMT. This method reduces the redundancy in phrase tables which is a direct effect of the phrase-based approach. A combination of PR-Enc with Huffman coding allows to reduce the size of an aggressively compressed phrase table by another 39 per...

In the last years, statistical machine translation has already demonstrated its usefulness within a wide variety of translation applications. In this line, phrasebased alignment models have become the reference to follow in order to build competitive systems. Finite state models are always an interesting framework because there are well-known efficient algorithms for their representation and ma...

In this paper, we describe several techniques to improve Korean-English statistical machine translation. We have built a phrase-based statistical machine translation system in a travel domain. On the baseline phrase-based system, several techniques are applied to improve the translation quality. Each technique can be applied or removed easily since the techniques are part of the preprocessing m...

This paper is based on the work carried out in the framework of the Verbmobil project, which is a limited-domain speech translation task (German-English). In the final evaluation, the statistical approach was found to perform best among five competing approaches. In this paper, we will further investigate the used statistical translation models. A shortcoming of the single-word based model is t...

Recent work in machine translation has evolved from the traditional word and phrase based models to include hierarchical phrase based and syntax-based models. These advances are motivated by the desire to integrate richer knowledge within the translation process to explicitly address limitations of the purely lexical phrasebased model. Generalized phrases as discussed in (Chiang, 2005) attempt ...

This master thesis aims to investigate a phrase-based approach of Memory-based Machine Translation. This is a form of automatic translation powered by lazy-learning classifiers to translate fragments of the input sentence. A parallel corpus serves as the basis for training such a classifier. In the phrase-based approach the principal component of these fragments is a phrase of arbitrary length....