Abstract
We present a scalable joint language model designed to utilize fine-grain syntactic tags. We discuss challenges such a design faces and describe our solutions that scale well to large tagsets and corpora. We advocate the use of relatively simple tags that do not require deep linguistic knowledge of the language but provide more structural information than POS tags and can be derived from automatically generated parse trees - a combination of properties that allows easy adoption of this model for new languages. We propose two fine-grain tagsets and evaluate our model using these tags, as well as POS tags and SuperARV tags in a speech recognition task and discuss future directions. © 2009 ACL and AFNLP.
Cite
CITATION STYLE
Filimonov, D., & Harper, M. (2009). A joint language model with fine-grain syntactic tags. In EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009 (pp. 1114–1123). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1699648.1699657
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