Search Results for author:
Found 7 papers, 1 papers with code
Combining Weakly Supervised ML Techniques for Low-Resource NLU
Accordingly, unsupervised learning and SSL (semi-supervised learning) techniques continue to be of vital importance.
Part of speech tagging for code switched data
We address the problem of Part of Speech tagging (POS) in the context of linguistic code switching (CS).
Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task
In the third shared task of the Computational Approaches to Linguistic Code-Switching (CALCS) workshop, we focus on Named Entity Recognition (NER) on code-switched social-media data.
Joint Part-of-Speech and Language ID Tagging for Code-Switched Data
Code-switching is the fluent alternation between two or more languages in conversation between bilinguals.
Crowdsourcing Universal Part-Of-Speech Tags for Code-Switching
We split the annotation task into three subtasks: one in which a subset of tokens are labeled automatically, one in which questions are specifically designed to disambiguate a subset of high frequency words, and a more general cascaded approach for the remaining data in which questions are displayed to the worker following a decision tree structure.
An urn model for majority voting in classification ensembles
An analysis of this classical urn model based on the hypergeometric distribution makes it possible to estimate the confidence on the outcome of majority voting when only a fraction of the individual predictions is known.
