Results 41 to 50 of about 4,220,052 (297)
Survey of Low-Resource Machine Translation [PDF]
We present a survey covering the state of the art in low-resource machine translation (MT) research. There are currently around 7,000 languages spoken in the world and almost all language pairs lack significant resources for training machine translation ...
B. Haddow+4 more
semanticscholar +1 more source
Pre-editing English news texts for machine translation into Russian
The paper discusses the possible advantages of pre-editing English news texts for machine translation into Russian. Pre-editing is defined as a process of adapting source text in order to reach a better quality of machine translation.
Елена Коканова+2 more
doaj +1 more source
Neural-based machine translation for medical text domain. Based on European Medicines Agency leaflet texts [PDF]
The quality of machine translation is rapidly evolving. Today one can find several machine translation systems on the web that provide reasonable translations, although the systems are not perfect. In some specific domains, the quality may decrease.
Marasek, Krzysztof, Wołk, Krzysztof
core +2 more sources
Evaluation of English–Slovak Neural and Statistical Machine Translation
This study is focused on the comparison of phrase-based statistical machine translation (SMT) systems and neural machine translation (NMT) systems using automatic metrics for translation quality evaluation for the language pair of English and Slovak.
Lucia Benkova+3 more
doaj +1 more source
Multi-View Network Representation Learning Algorithm Research
Network representation learning is a key research field in network data mining. In this paper, we propose a novel multi-view network representation algorithm (MVNR), which embeds multi-scale relations of network vertices into the low dimensional ...
Zhonglin Ye+3 more
doaj +1 more source
Google Translate and DeepL: Breaking taboos in translator training. Observational study and analysis
In recent decades, when we read about the use of machine translation, we were told that it was not suitable for professional translation. The reason was that machine translation used to produce poor results as long as it was not applied to controlled ...
María-José Varela Salinas, Ruth Burbat
doaj +1 more source
A Systematic Comparison of Data Selection Criteria for SMT Domain Adaptation
Data selection has shown significant improvements in effective use of training data by extracting sentences from large general-domain corpora to adapt statistical machine translation (SMT) systems to in-domain data.
Longyue Wang+4 more
doaj +1 more source
Bleu: a Method for Automatic Evaluation of Machine Translation
Human evaluations of machine translation are extensive but expensive. Human evaluations can take months to finish and involve human labor that can not be reused.
K. Papineni+3 more
semanticscholar +1 more source
With the rapid development of machine translation (MT), the MT evaluation becomes very important to timely tell us whether the MT system makes any progress.
Aaron L.-F. Han+4 more
doaj +1 more source
A Relationship: Word Alignment, Phrase Table, and Translation Quality
In the last years, researchers conducted several studies to evaluate the machine translation quality based on the relationship between word alignments and phrase table.
Liang Tian+3 more
doaj +1 more source