Code-mixing is a frequent communication style among multilingual speakers where they mix words and phrases from two different languages in the same utterance of text or speech. Identifying and filtering code-mixed text is a challenging task due to its co-existence with monolingual and noisy text. Over the years, several code-mixing metrics have been extensively used to identify and validate code-mixed text quality. This paper demonstrates several inherent limitations of code-mixing metrics with examples from the already existing datasets that are popularly used across various experiments.
@article{arxiv.2106.10123,
title = {Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text},
author = {Vivek Srivastava and Mayank Singh},
journal= {arXiv preprint arXiv:2106.10123},
year = {2021}
}