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Abstract
In the last year, we have seen a lot of evidence about the superiority of neural
machine translation approaches (NMT) over phrase-based statistical approaches
(PBMT). This trend has shown for the general domain at public competitions such as the WMT challenges as well as in the obvious quality increase in online translation services that have changed their technology. In this paper, we take the perspective of an LSP. The questions we want to answer with this study is if now is already the time to invest in the new technology. To answer this question, we have collected evidence as to whether an existing state of-the-art NMT system for the general domain can already compete with a domain trained and optimised Moses (PBMT) system or if it is maybe already better. As it is well known that automatic quality measures are not reliable for comparing the performance of different system types, we have performed a detailed manual evaluation based on a test suite of domain segments.
machine translation approaches (NMT) over phrase-based statistical approaches
(PBMT). This trend has shown for the general domain at public competitions such as the WMT challenges as well as in the obvious quality increase in online translation services that have changed their technology. In this paper, we take the perspective of an LSP. The questions we want to answer with this study is if now is already the time to invest in the new technology. To answer this question, we have collected evidence as to whether an existing state of-the-art NMT system for the general domain can already compete with a domain trained and optimised Moses (PBMT) system or if it is maybe already better. As it is well known that automatic quality measures are not reliable for comparing the performance of different system types, we have performed a detailed manual evaluation based on a test suite of domain segments.
Original language | English |
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Title of host publication | EAMT 2017: The 20th Annual Conference of the European Association for Machine Translation |
Number of pages | 6 |
Publication status | Published - 31 May 2017 |
Event | 20th Annual Conference of the European Association for Machine Translation - Prague, Czech Republic Duration: 29 May 2017 → 31 May 2017 https://ufal.mff.cuni.cz/eamt2017/ |
Conference
Conference | 20th Annual Conference of the European Association for Machine Translation |
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Abbreviated title | EAMT 2017 |
Country/Territory | Czech Republic |
City | Prague |
Period | 29/05/17 → 31/05/17 |
Internet address |
Projects
- 1 Finished