Automatic Translations Versus Human Translations in Nowadays World

Automatic Generation of Model Translations

The translation of information between heterogeneous representations is a long standing issue. With the large spreading of cooperative applications fostered by the advent of the Internet the problem has gained more and more attention but there are still few and partial solutions. In general, given an information source, different translations can be defined for the same target model. In this wo...

Automatic Detection of Omissions in Translations

ADOMIT is an algorithm for Automatic Detection of OMIssions in Translations. The algorithm relies solely on geometric analysis of bitext maps and uses no linguistic information. This property allows it to deal equally well with omissions that do not correspond to linguistic units, such as might result from word-processing mishaps. ADOMIT has proven itself by discovering many errors in a hand-co...

From Human Evaluation to Automatic Selection of Good Translations

In this paper we describe a machine learning method tailored to overcome the difficulty of selecting and putting together translated segments in the Verbmobil system. We use off line human feedback to determine an optimized confidence rescaling scheme for the confidence values provided by four independent and competing translation paths in Verbmobil.

Translations

TransCheck - or the automatic validation of human translations

Translators, like all people who draft a lot of texts, will commonly run a spelling or style checker on their translations before delivering them, in the hope of detecting simple kinds of errors they may have overlooked. Because these writing aids are monolingual, however, they are entirely useless in detecting even the most flagrant kinds of translation errors, since these are bilingual in nat...