![]() ![]() These strategies are not constrained by in-domain annotations, rather they leverage pre-existing monolingual annotated resources for training. In this paper, we propose efficient and less resource-intensive strategies for parsing of code-mixed data. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short PapersĪssociation for Computational Linguistics Joining Hands: Exploiting Monolingual Treebanks for Parsing of Code-mixing Data Due to lack of an evaluation set for code-mixed structures, we also present a data set of 450 Hindi and English code-mixed tweets of Hindi multilingual speakers for evaluation.", ![]() We show that these methods can produce significantly better results as compared to an informed baseline. Publisher = "Association for Computational Linguistics",Ībstract = "In this paper, we propose efficient and less resource-intensive strategies for parsing of code-mixed data. Cite (Informal): Joining Hands: Exploiting Monolingual Treebanks for Parsing of Code-mixing Data (Bhat et al., EACL 2017) Copy Citation: BibTeX Markdown MODS XML Endnote More options… PDF: = "Joining Hands: Exploiting Monolingual Treebanks for Parsing of Code-mixing Data",īooktitle = "Proceedings of the 15th Conference of the uropean Chapter of the Association for Computational Linguistics: Volume 2, Short Papers", Association for Computational Linguistics. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 324–330, Valencia, Spain. Joining Hands: Exploiting Monolingual Treebanks for Parsing of Code-mixing Data. Bhat, Manish Shrivastava, and Dipti Sharma. Anthology ID: E17-2052 Volume: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers Month: April Year: 2017 Address: Valencia, Spain Venue: EACL SIG: Publisher: Association for Computational Linguistics Note: Pages: 324–330 Language: URL: DOI: Bibkey: bhat-etal-2017-joining Cite (ACL): Irshad Bhat, Riyaz A. Due to lack of an evaluation set for code-mixed structures, we also present a data set of 450 Hindi and English code-mixed tweets of Hindi multilingual speakers for evaluation. Abstract In this paper, we propose efficient and less resource-intensive strategies for parsing of code-mixed data. ![]()
0 Comments
Leave a Reply. |