Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text

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Abstract

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.

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Srivastava, V., & Singh, M. (2021). Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text. In Computational Approaches to Linguistic Code-Switching, CALCS 2021 - Proceedings of the 5th Workshop (pp. 6–14). Association for Computational Linguistics (ACL). https://doi.org/10.26615/978-954-452-056-4_002

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