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Found 7 papers, 1 papers with code
Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation
The study covers eight language pairs, different training corpus sizes, two architectures, and three types of annotation: dummy tags (with no linguistic information at all), part-of-speech tags, and morpho-syntactic description tags, which consist of part of speech and morphological features.
The Universitat d'Alacant Submissions to the English-to-Kazakh News Translation Task at WMT 2019
This paper describes the two submissions of Universitat d{'}Alacant to the English-to-Kazakh news translation task at WMT 2019.
Prompsit's submission to WMT 2018 Parallel Corpus Filtering shared task
This paper describes Prompsit Language Engineering{'}s submissions to the WMT 2018 parallel corpus filtering shared task.
Sharing resources between free/open-source rule-based machine translation systems: Grammatical Framework and Apertium
In this paper, we describe two methods developed for sharing linguistic data between two free and open source rule based machine translation systems: Apertium, a shallow-transfer system; and Grammatical Framework (GF), which performs a deeper syntactic transfer.
Source-Language Dictionaries Help Non-Expert Users to Enlarge Target-Language Dictionaries for Machine Translation
In this paper, a previous work on the enlargement of monolingual dictionaries of rule-based machine translation systems by non-expert users is extended to tackle the complete task of adding both source-language and target-language words to the monolingual dictionaries and the bilingual dictionary.
