First experiments and results in English-Hungarian neural machine translation
Neural machine translation (NMT) has emerged recently as a promising alternative of standard rule-based or phrase-based statistical approaches especially for languages which have so far been considered challenging for the two paradigms. Since Hungarian has long been one of these challenging language...
Elmentve itt :
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| Dokumentumtípus: | Könyv része |
| Megjelent: |
2017
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| Sorozat: | Magyar Számítógépes Nyelvészeti Konferencia
13 |
| Kulcsszavak: | Nyelvészet - számítógép alkalmazása |
| Online Access: | http://acta.bibl.u-szeged.hu/59016 |
| Tartalmi kivonat: | Neural machine translation (NMT) has emerged recently as a promising alternative of standard rule-based or phrase-based statistical approaches especially for languages which have so far been considered challenging for the two paradigms. Since Hungarian has long been one of these challenging languages, it is a natural candidate for neural machine translation to explore whether this approach can bring some improvement in a task which translation models have so far been unable to cope with. The paper presents our first results of applying neural models to English to Hungarian translation and shows that with the right configuration and data preparation, publicly available NMT implementations can significantly outperform the previous state-of-the-art systems on standard benchmarks. |
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| Terjedelem/Fizikai jellemzők: | 275-286 |
| ISBN: | 978-963-306-518-1 |