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Found 19 papers, 4 papers with code
A multi-source approach for Breton–French hybrid machine translation
Corpus-based approaches to machine translation (MT) have difficulties when the amount of parallel corpora to use for training is scarce, especially if the languages involved in the translation are highly inflected.
An English-Swahili parallel corpus and its use for neural machine translation in the news domain
This paper describes our approach to create a neural machine translation system to translate between English and Swahili (both directions) in the news domain, as well as the process we followed to crawl the necessary parallel corpora from the Internet.
Bicleaner at WMT 2020: Universitat d’Alacant-Prompsit’s submission to the parallel corpus filtering shared task
This paper describes the joint submission of Universitat d’Alacant and Prompsit Language Engineering to the WMT 2020 shared task on parallel corpus filtering.
MultiTraiNMT: Training Materials to Approach Neural Machine Translation from Scratch
The MultiTraiNMT Erasmus+ project aims at developing an open innovative syllabus in neural machine translation (NMT) for language learners and translators as multilingual citizens.
Fuzzy-match repair using black-box machine translation systems: what can be expected?
Computer-aided translation (CAT) tools often use a translation memory (TM) as the key resource to assist translators.
MultitraiNMT Erasmus+ project: Machine Translation Training for multilingual citizens (multitrainmt.eu)
The MultitraiNMT Erasmus+ project has developed an open innovative syl-labus in machine translation, focusing on neural machine translation (NMT) and targeting both language learners and translators.
GoURMET – Machine Translation for Low-Resourced Languages
The GoURMET project, funded by the European Commission’s H2020 program (under grant agreement 825299), develops models for machine translation, in particular for low-resourced languages.
Smart Bilingual Focused Crawling of Parallel Documents
Crawling parallel texts $\unicode{x2014}$texts that are mutual translations$\unicode{x2014}$ from the Internet is usually done following a brute-force approach: documents are massively downloaded in an unguided process, and only a fraction of them end up leading to actual parallel content.
Curated Datasets and Neural Models for Machine Translation of Informal Registers between Mayan and Spanish Vernaculars
The Mayan languages comprise a language family with an ancient history, millions of speakers, and immense cultural value, that, nevertheless, remains severely underrepresented in terms of resources and global exposure.
Non-Fluent Synthetic Target-Language Data Improve Neural Machine Translation
When the amount of parallel sentences available to train a neural machine translation is scarce, a common practice is to generate new synthetic training samples from them.
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.
Cross-lingual neural fuzzy matching for exploiting target-language monolingual corpora in computer-aided translation
The paper presents an automatic evaluation of these techniques on four language pairs that shows that our approach can successfully exploit monolingual texts in a TM-based CAT environment, increasing the amount of useful translation proposals, and that our neural model for estimating the post-editing effort enables the combination of translation proposals obtained from monolingual corpora and from TMs in the usual way.
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach
Many DA approaches aim at expanding the support of the empirical data distribution by generating new sentence pairs that contain infrequent words, thus making it closer to the true data distribution of parallel sentences.
Learning synchronous context-free grammars with multiple specialised non-terminals for hierarchical phrase-based translation
Translation models based on hierarchical phrase-based statistical machine translation (HSMT) have shown better performances than the non-hierarchical phrase-based counterparts for some language pairs.
UAlacant machine translation quality estimation at WMT 2018: a simple approach using phrase tables and feed-forward neural networks
We describe the Universitat d'Alacant submissions to the word- and sentence-level machine translation (MT) quality estimation (QE) shared task at WMT 2018.
Generalized Biwords for Bitext Compression and Translation Spotting
For example, a bitext can be seen as a sequence of biwords ---pairs of parallel words with a high probability of co-occurrence--- that can be used as an intermediate representation in the compression process.
Inferring Shallow-Transfer Machine Translation Rules from Small Parallel Corpora
This paper describes a method for the automatic inference of structural transfer rules to be used in a shallow-transfer machine translation (MT) system from small parallel corpora.
An open diachronic corpus of historical Spanish: annotation criteria and automatic modernisation of spelling
The IMPACT-es diachronic corpus of historical Spanish compiles over one hundred books --containing approximately 8 million words-- in addition to a complementary lexicon which links more than 10 thousand lemmas with attestations of the different variants found in the documents.
