Translation Mining: Definiteness across Languages (A Reply to Jenks 2018)

Translation and Extension of Concepts Across Languages

We present a method which, given a few words defining a concept in some language, retrieves, disambiguates and extends corresponding terms that define a similar concept in another specified language. This can be very useful for cross-lingual information retrieval and the preparation of multi-lingual lexical resources. We automatically obtain term translations from multilingual dictionaries and ...

Metacognitive (Rending) Strategies Across Languages and Techniques

Definiteness and Number in Japanese to German Machine Translation

A signiicant problem when translating Japanese dialogues into German is the missing information on number and deeniteness in the Japanese analysis output. The integration of the search for such information into the transfer process provides an eecient solution. Transfer rules, preference rules and default rules are combined. Thereby, grammatical and lexical knowledge of the source language, kno...

Not lost in translation: neural responses shared across languages.

How similar are the brains of listeners who hear the same content expressed in different languages? We directly compared the fMRI response time courses of English speakers and Russian speakers who listened to a real-life Russian narrative and its English translation. In the translation, we tried to preserve the content of the narrative while reducing the structural similarities across languages...

Optimizing Tokenization Choice for Machine Translation across Multiple Target Languages

Tokenization is very helpful for StatisticalMachine Translation (SMT), especiallywhen translating from morphologically rich languages. Typically, a single tokenization scheme is applied to the entire source-language text and regardless of the target language. In this paper, we evaluate the hypothesis that SMT performance may benefit from different tokenization schemes for different words within...