@inproceedings{srivastava-singh-2021-challenges,
title = "Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text",
author = "Srivastava, Vivek and
Singh, Mayank",
editor = "Solorio, Thamar and
Chen, Shuguang and
Black, Alan W. and
Diab, Mona and
Sitaram, Sunayana and
Soto, Victor and
Yilmaz, Emre and
Srinivasan, Anirudh",
booktitle = "Proceedings of the Fifth Workshop on Computational Approaches to Linguistic Code-Switching",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.calcs-1.2",
doi = "10.18653/v1/2021.calcs-1.2",
pages = "6--14",
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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%0 Conference Proceedings
%T Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text
%A Srivastava, Vivek
%A Singh, Mayank
%Y Solorio, Thamar
%Y Chen, Shuguang
%Y Black, Alan W.
%Y Diab, Mona
%Y Sitaram, Sunayana
%Y Soto, Victor
%Y Yilmaz, Emre
%Y Srinivasan, Anirudh
%S Proceedings of the Fifth Workshop on Computational Approaches to Linguistic Code-Switching
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F srivastava-singh-2021-challenges
%X 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.
%R 10.18653/v1/2021.calcs-1.2
%U https://aclanthology.org/2021.calcs-1.2
%U https://doi.org/10.18653/v1/2021.calcs-1.2
%P 6-14
Markdown (Informal)
[Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text](https://aclanthology.org/2021.calcs-1.2) (Srivastava & Singh, CALCS 2021)
ACL