Findings of the 2017 conference on machine translation (wmt17)
This paper presents the results of the WMT17 shared tasks, which included three machine
translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and …
translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and …
Neural machine translation with extended context
We investigate the use of extended context in attention-based neural machine translation.
We base our experiments on translated movie subtitles and discuss the effect of increasing …
We base our experiments on translated movie subtitles and discuss the effect of increasing …
Trivial transfer learning for low-resource neural machine translation
Transfer learning has been proven as an effective technique for neural machine translation
under low-resource conditions. Existing methods require a common target language …
under low-resource conditions. Existing methods require a common target language …
[PDF][PDF] OpenSubtitles2018: Statistical rescoring of sentence alignments in large, noisy parallel corpora
Movie and TV subtitles are a highly valuable resource for the compilation of parallel corpora
thanks to their availability in large numbers and across many languages. However, the …
thanks to their availability in large numbers and across many languages. However, the …
Driver fatigue transition prediction in highly automated driving using physiological features
One of the main causes of traffic accidents is driver fatigue due to monotonous driving, sleep
deprivation, boredom, or a combination of these. Thus, fatigue detection systems have been …
deprivation, boredom, or a combination of these. Thus, fatigue detection systems have been …
The MeMAD submission to the WMT18 multimodal translation task
This paper describes the MeMAD project entry to the WMT Multimodal Machine Translation
Shared Task. We propose adapting the Transformer neural machine translation (NMT) …
Shared Task. We propose adapting the Transformer neural machine translation (NMT) …
Why don't people use character-level machine translation?
We present a literature and empirical survey that critically assesses the state of the art in
character-level modeling for machine translation (MT). Despite evidence in the literature that …
character-level modeling for machine translation (MT). Despite evidence in the literature that …
A product and process analysis of post-editor corrections on neural, statistical and rule-based machine translation output
M Koponen, L Salmi, M Nikulin - Machine Translation, 2019 - Springer
This paper presents a comparison of post-editing (PE) changes performed on English-to-
Finnish neural (NMT), rule-based (RBMT) and statistical machine translation (SMT) output …
Finnish neural (NMT), rule-based (RBMT) and statistical machine translation (SMT) output …
Corpus based machine translation system with deep neural network for Sanskrit to Hindi translation
Sanskrit language is the mother of almost all Indian languages. The main requirement in
Sanskrit domain is to translate the life-transforming stories (epics), Vedas etc. to make them …
Sanskrit domain is to translate the life-transforming stories (epics), Vedas etc. to make them …
Enhancing Low-Resource Sanskrit-Hindi Translation through Deep Learning with Ayurvedic Text
The Machine Translation (MT) community is interested in Neural Machine Translation (NMT)
because it can persevere continues data over a range of input and output phrase lengths …
because it can persevere continues data over a range of input and output phrase lengths …