Abstract / Description of output
This paper describes a hybrid Machine Translation (MT) system built for translating from English to German in the domain of technical documentation. The system is based on three different MT engines (phrase-based SMT, RBMT, neural) that are joined by a selection mechanism that uses deep linguistic features within a machine learning process. It also presents a detailed source-driven manual error analysis we have performed using a dedicated “test suite” that contains selected examples of relevant phenomena. While automatic scores show huge differences between the engines, the overall average number or errors they (do not) make is very similar for all systems. However, the detailed error breakdown shows that the systems behave very differently concerning the various phenomena.
Original language | English |
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Title of host publication | Proceedings of the 2nd Deep Machine Translation Workshop |
Place of Publication | Lisbon, Portugal |
Publisher | ÚFAL MFF UK |
Pages | 29-38 |
Number of pages | 10 |
ISBN (Electronic) | 978-80-88132-02-8 |
Publication status | Published - 21 Oct 2016 |
Event | Deep Machine Translation Workshop 2016 - Lisboa, Portugal Duration: 21 Oct 2016 → 21 Oct 2016 http://deepmt2016.di.fc.ul.pt/ |
Workshop
Workshop | Deep Machine Translation Workshop 2016 |
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Abbreviated title | DMTW 2016 |
Country/Territory | Portugal |
City | Lisboa |
Period | 21/10/16 → 21/10/16 |
Internet address |