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        <title>Cross-Lingual Syntactic Transfer with Limited Resources</title>
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        <namePart type="given">Mohammad</namePart>
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    <abstract>We describe a simple but effective method for cross-lingual syntactic transfer of dependency parsers, in the scenario where a large amount of translation data is not available. This method makes use of three steps: 1) a method for deriving cross-lingual word clusters, which can then be used in a multilingual parser; 2) a method for transferring lexical information from a target language to source language treebanks; 3) a method for integrating these steps with the density-driven annotation projection method of Rasooli and Collins (2015). Experiments show improvements over the state-of-the-art in several languages used in previous work, in a setting where the only source of translation data is the Bible, a considerably smaller corpus than the Europarl corpus used in previous work. Results using the Europarl corpus as a source of translation data show additional improvements over the results of Rasooli and Collins (2015). We conclude with results on 38 datasets from the Universal Dependencies corpora.</abstract>
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    <identifier type="doi">10.1162/tacl_a_00061</identifier>
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%0 Journal Article
%T Cross-Lingual Syntactic Transfer with Limited Resources
%A Rasooli, Mohammad Sadegh
%A Collins, Michael
%J Transactions of the Association for Computational Linguistics
%D 2017
%V 5
%I MIT Press
%C Cambridge, MA
%F rasooli-collins-2017-cross
%X We describe a simple but effective method for cross-lingual syntactic transfer of dependency parsers, in the scenario where a large amount of translation data is not available. This method makes use of three steps: 1) a method for deriving cross-lingual word clusters, which can then be used in a multilingual parser; 2) a method for transferring lexical information from a target language to source language treebanks; 3) a method for integrating these steps with the density-driven annotation projection method of Rasooli and Collins (2015). Experiments show improvements over the state-of-the-art in several languages used in previous work, in a setting where the only source of translation data is the Bible, a considerably smaller corpus than the Europarl corpus used in previous work. Results using the Europarl corpus as a source of translation data show additional improvements over the results of Rasooli and Collins (2015). We conclude with results on 38 datasets from the Universal Dependencies corpora.
%R 10.1162/tacl_a_00061
%U https://aclanthology.org/Q17-1020/
%U https://doi.org/10.1162/tacl_a_00061
%P 279-293

Markdown (Informal)

[Cross-Lingual Syntactic Transfer with Limited Resources](https://aclanthology.org/Q17-1020/) (Rasooli & Collins, TACL 2017)

• Cross-Lingual Syntactic Transfer with Limited Resources (Rasooli & Collins, TACL 2017)

ACL

• Mohammad Sadegh Rasooli and Michael Collins. 2017. Cross-Lingual Syntactic Transfer with Limited Resources. Transactions of the Association for Computational Linguistics, 5:279–293.