User-friendly text prediction for translators

Abstract

Text prediction is a form of interactive machine translation that is well suited to skilled translators. In principle it can assist in the production of a target text with minimal disruption to a translator's normal routine. However, recent evaluations of a prototype prediction system showed that it significantly decreased the productivity of most translators who used it. In this paper, we analyze the reasons for this and propose a solution which consists in seeking predictions that maximize the expected benefit to the translator, rather than just trying to anticipate some amount of upcoming text. Using a model of a "typical translator" constructed from data collected in the evaluations of the prediction prototype, we show that this approach has the potential to turn text prediction into a help rather than a hindrance to a translator.

How Much Information Does a Human Translator Add to the Original?

“…Subsequently, research moved to extrinsic evaluation of translation models, in the context of end-to-end machine translation. Foster et al (2002) and others have used prediction to propose auto-completions to speed up human translation. As we have seen, prediction and compression are highly related.…”

Confidence estimation for NLP applications

“…To establish usability improvements in terms of timing speed due to the use of the CE layer we use a user-model simulation [Foster et al 2002] (section 6.2.4). For a prediction of a given length, this model gives the time benefit to the user if the prediction is correct, as well as the cost if it is not.…”

PRIMT: A Pick-Revise Framework for Interactive Machine Translation

“…In many cases, PE needs a lot of modifications, which is time-consuming (Plitt and Masselot, 2010). To speed up the process, interactive machine translation (IMT) is proposed which instantly update the translation result after every human action (Langlais et al, 2000;Foster et al, 2002;Barrachina et al, 2009;Koehn, 2009;González-Rubio et al, 2013;. Because the translation quality could be improved after every update, IMT is expected to generate high quality translations with less human actions (Sanchis-Trilles et al, 2014).…”