Post-editing is an increasingly common form of human-machine cooperation for translation. One possible support for the post-editing task is offering several machine outputs to a human translator from which then can choose the most suitable one. This paper investigates the selection process for such method to get a better insight into it so that it can be optimally automatised in future work. Ex...

Word Confidence Estimation (WCE) for machine translation (MT) or automatic speech recognition (ASR) consists in judging each word in the (MT or ASR) hypothesis as correct or incorrect by tagging it with an appropriate label. In the past, this task has been treated separately in ASR or MT contexts and we propose here a joint estimation of word confidence for a spoken language translation (SLT) t...

Those of you who attended the 1981 conference Practical Experience of Machine Translation* may have been somewhat surprised to see how much could be said at the time by speakers who in many cases had only very limited experience of practical machine translation (MT). Many must have had their doubts about the usefulness of the systems presented, while others must have been more than just a littl...

The Language Translation Interface (LTI) is a prototype developed for the Australian Defence Organisation. The aim is provide a single, simple, interface to a variety of MT tools and utilities for personnel who need to produce translations when they have no easy access to human translators. Now that the LTI has been demonstrated and trialled at several military exercises, we are gathering user ...

Background: Diabetes is a major health crisis for Hispanics and Asian Americans. Moreover, Spanish and Chinese speakers are more likely to have limited English proficiency in the United States. One potential tool for facilitating language communication between diabetes patients and health care providers is technology, specifically mobile phones. Objective: Previous studies have assessed machine...

Although significant improvements have been achieved in statistical machine translation (SMT), even the best machine translation technology is far from competing with human translators. An alternative approach to obtain high quality translation is to use a human translator who is assisted by an SMT. In interactive-predictive computer-assisted translation (IPCAT) paradigm, the human translator b...

It is today acknowledged that neural network language models outperform backoff language models in applications like speech recognition or statistical machine translation. However, training these models on large amounts of data can take several days. We present efficient techniques to adapt a neural network language model to new data. Instead of training a completely new model or relying on mix...

We explore the problem of integrating a phrase-based MT system within a computerassisted translation (CAT) environment. We argue that one way of achieving successful integration is to design an MT system that behaves more like the translation memory (TM) component of CAT systems. This implies producing MT output that is consistent with that of a TM when high-similarity material exists in the tr...

In this presentation I will discuss the design and implementation of Let’s MT!, a collaborative platform for building statistical machine translation systems. The goal of this platform is to make MT technology, that has been developed in academia, accessible for professional translators, freelancers and every-day users without requiring technical skills and deep background knowledge of the appr...