We describe an open-source toolkit for statistical machine translation whose novel
contributions are (a) support for linguistically motivated factors,(b) confusion network …

Abstract Evaluation of machine translation output is an important but difficult task. Over the
last years, a variety of automatic evaluation measures have been studied, some of them like …

Research into the translation of the output of automatic speech recognition (ASR) systems is
hindered by the dearth of datasets developed for that explicit purpose. For SpanishEnglish …

Text-to-SQL task maps natural language utterances to structured queries that can be issued
to a database. State-of-the-art (SOTA) systems rely on finetuning large, pre-trained language …

We present discriminative reordering models for phrase-based statistical machine
translation. The models are trained using the maximum entropy principle. We use several …

In this work we investigate new possibilities for improving the quality of statistical machine
translation (SMT) by applying word reorderings of the source language sentences based on …

Currently most statistical machine translation systems make use of alignments as a first step
in the process of training the actual translation models. Several researchers have …

This paper reports an overview of the evaluation campaign results of the IWSLT 2005
workshop1. The BTEC corpus, which consists of typical travel domain phrases, was used …

German compound words pose special problems to statistical machine translation systems:
the occurence of each of the components in the training data is not sufficient for successful …

We present a novel approach for the automatic translation of written text into sign language.
A new corpus focussing on the weather report domain for the language pair German and …