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

Vivek Srivastava, Mayank Singh

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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 codemixed 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.

Topics & Concepts

Computer scienceCode (set theory)Code-mixingUtteranceNatural language processingMixing (physics)Task (project management)Artificial intelligenceCode-switchingProgramming languageLinguisticsSet (abstract data type)ManagementPhysicsQuantum mechanicsEconomicsPhilosophyNatural Language Processing TechniquesAuthorship Attribution and ProfilingText Readability and Simplification
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