The merit of phrase-based statistical machine translation is often reduced by the complexity to construct it. In this paper, we address some issues in phrase-based statistical machine translation, namely: the size of the phrase translation table, the use of underlying translation model probability and the length of the phrase unit. We present Level-Of-Detail (LOD) approach, an agglomerative app...

This paper deals with the underspeciied semantic representation of ellipsis and its resolution. We present an analysis to explain the the distribution of strict and sloppy readings in the interaction of verb phrase ellipsis and anaphora. The analysis is integrated into a framework that enables a uniform and underspeciied treatment of scope, anaphora and VPE. Abstract This paper deals with the u...

A typical phrase-based machine translation (PBMT) system uses phrase pairs extracted from word-aligned parallel corpora. All phrase pairs that are consistent with word alignments are collected. The resulting phrase table is very large and includes many non-syntactic phrases which may not be necessary. We propose to filter the phrase table based on source language syntactic constraints. Rather t...

Phrase based language models have been recognized to have an advantage over word based language models since they allow us to capture long span ning dependencies Class based language models have been used to improve model generalization and overcome problems with data sparseness In this pa per we present a novel approach for combining the phrase acquisition with class construction process to au...