Papers with Turkish-German

1 papers
Lexical Normalization for Code-switched Data and its Effect on POS Tagging (2021.eacl-main)

Copied to clipboard

Challenge: Social media data can be used to improve natural language processing performance, but it is often overlooked by lexical normalization systems.
Approach: They propose three lexical normalization models specifically designed to handle code-switched data and evaluate their performance on POS tags.
Outcome: The proposed models outperform monolingual models and lead to 5.4% performance increase for POS tagging compared to unnormalized input.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations