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Improving SMT quality with morpho-syntactic analysis
Open accessAbstract
In the framework of statistical machine translation (SMT), correspondences between the words in the source and the target language are learned from bilingual corpora on the basis of so-called alignment models. Many of the statistical systems use little or no linguistic knowledge to structure the underlying models. In this paper we argue that training data is typically not large enough to sufficiently represent the range of different phenomena in natural languages and that SMT can take advantage of the explicit introduction of some knowledge about the languages under consideration. The improvement of the translation results is demonstrated on two different German-English corpora.
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Segmentation of morphologically complex words such as compounds is widely used for SMT.
“The segmentation of morphologically complex words such as compounds is widely used for SMT, and various algorithms for morpheme segmentation have been investigated (Nießen and Ney, 2000;Koehn and Knight, 2003;Virpioja et al., 2007;Stallard et al., 2012).”
From Neural Machine Translation of Rare Words with Subword Units (2016) · cites this paper as Nießen and Ney, 2000
The German Compound Words section says the authors split German compounds into their components for statistical machine translation, and the Results section reports an improvement from splitting compounds. This supports the cited paper as an example of compound segmentation in SMT, but it does not establish that segmentation is widely used or that this paper investigated various morpheme-segmentation algorithms. (LLM, conf=0.84)
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Research works printed but not linked: 8
- P.F. Brown, S.A. Della Pietra, V.J. Della Pietra, and ILL. Mercer. 1993. Mathematics of Statistical Machine %'ansla- tion: Parameter Estimation. Computational Linguistics, 19(2):263 311.
- Fred Karlsson. 1990. Constraint Grmnmar as a Frainework tbr Parsing Running Text. In PTvecedings of th, e 13th, hzternational Confer- cnce on Computational Linguistics, volume 3, pages 168-173, Helsinki, Finland.
- Sonja Niefien, Stephan Vogel, Hermann Ney, and Christoph Tilhnann. 1998. A DP based Search Algorithm tbr Statistical Machine Translation. In Proceedings of the 36th An- nual Con:ferencc of the Association for Com- putational Linguistics and the 17th Interna- tional Conference on Computational Linguis- ties, pages 960 967, Montrdal, P.Q., Canada, August.
- Sonja Niefien, Franz loser Oeh, Gregor Leusch, and Hermaml Ney. 2000. An Ewfluation Tool tbr Machine %'anslation: Fast Evaluation for MT Research. In Proceedings of the 2nd International Conference on Language Rc- so'arccs and Evaluation, pages 39 45, Athens, Greece, May.
- Franz .losef Och and Hans Weber. 1998. hn- t)roving Statistical Natural Language ~:ans- lation with Categories and Rules. In Pro- eccdings of the 36th Annual Con.fcrcncc of th, e Association for Computational Linguis- tics and the 17th international Conference on Computational Linguistics, pages 985-989, Montrdal, P.Q., Canada, August.
- Iq:anz ,loser Och, Christol)h Tillmmm, aim Her- maml Ney. 1999. hnproved Alignment Mod- els tbr Statistical Machine Translation. In Proceedings of the Co~:ference on Empirical Methods in Natu~nl Language Processing and Very Large Corpora, pages 20-28, University of Maryland, College Park, Maryland, June.
- Wolfgang Wahlster. 1993. Verl)mobih Transla- lion of Face-to-Face Dialogs. In Proceedings of the MT Summit IV, pages 127-135, Kobe, Japan.
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Cited by
Sorted by citations
Neural Machine Translation of Rare Words with Subword Units
Sennrich, R., Haddow, B., & Birch, A. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p16-1162 · Cited by 974
Neural Machine Translation with Byte-Level Subwords
Wang, C., Cho, K., & Gu, J. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i05.6451 · Cited by 147
Metadata
- Authors
- Nießen, S., & Ney, H.
- Affiliations
- RWTH Aachen University (DE)
- Venue
- Proceedings of the 18th conference on Computational linguistics -
- Published
- 2000
- Volume
- 2
- Pages
- 1081
- ISSN
- 1525-2477 (ISSN-L)
- OpenAlex
- W2015350341
- Cited by
- 80
- References
- 0
- Citations by year
- 2024: 1 · 2023: 1 · 2021: 2 · 2020: 1 · 2018: 5 · 2017: 2 · 2016: 3 · 2015: 2 · 2014: 8 · 2013: 4 · 2012: 3
- FWCI
- 2.88
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Computational Linguistics (publishedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Social Sciences › Arts and Humanities › Language and Linguistics › Translation Studies and Practices
- Keywords
- statistical machine translation, morphosyntactic analysis, alignment model, bilingual corpus, German-English translation, translation quality
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