@inproceedings{shahiki-tash-etal-2022-word,
title = "Word Level Language Identification in Code-mixed {K}annada-{E}nglish Texts using traditional machine learning algorithms",
author = "Shahiki Tash, M. and
Ahani, Z. and
Tonja, A.l. and
Gemeda, M. and
Hussain, N. and
Kolesnikova, O.",
editor = "Chakravarthi, Bharathi Raja and
Murugappan, Abirami and
Chinnappa, Dhivya and
Hane, Adeep and
Kumeresan, Prasanna Kumar and
Ponnusamy, Rahul",
booktitle = "Proceedings of the 19th International Conference on Natural Language Processing (ICON): Shared Task on Word Level Language Identification in Code-mixed Kannada-English Texts",
month = dec,
year = "2022",
address = "IIIT Delhi, New Delhi, India",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.icon-wlli.5",
pages = "25--28",
abstract = "Language Identification at the Word Level in Kannada-English Texts. This paper de- scribes the system paper of CoLI-Kanglish 2022 shared task. The goal of this task is to identify the different languages used in CoLI- Kanglish 2022. This dataset is distributed into different categories including Kannada, En- glish, Mixed-Language, Location, Name, and Others. This Code-Mix was compiled by CoLI- Kanglish 2022 organizers from posts on social media. We use two classification techniques, KNN and SVM, and achieve an F1-score of 0.58 and place third out of nine competitors.",
}
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%0 Conference Proceedings
%T Word Level Language Identification in Code-mixed Kannada-English Texts using traditional machine learning algorithms
%A Shahiki Tash, M.
%A Ahani, Z.
%A Tonja, A.l.
%A Gemeda, M.
%A Hussain, N.
%A Kolesnikova, O.
%Y Chakravarthi, Bharathi Raja
%Y Murugappan, Abirami
%Y Chinnappa, Dhivya
%Y Hane, Adeep
%Y Kumeresan, Prasanna Kumar
%Y Ponnusamy, Rahul
%S Proceedings of the 19th International Conference on Natural Language Processing (ICON): Shared Task on Word Level Language Identification in Code-mixed Kannada-English Texts
%D 2022
%8 December
%I Association for Computational Linguistics
%C IIIT Delhi, New Delhi, India
%F shahiki-tash-etal-2022-word
%X Language Identification at the Word Level in Kannada-English Texts. This paper de- scribes the system paper of CoLI-Kanglish 2022 shared task. The goal of this task is to identify the different languages used in CoLI- Kanglish 2022. This dataset is distributed into different categories including Kannada, En- glish, Mixed-Language, Location, Name, and Others. This Code-Mix was compiled by CoLI- Kanglish 2022 organizers from posts on social media. We use two classification techniques, KNN and SVM, and achieve an F1-score of 0.58 and place third out of nine competitors.
%U https://aclanthology.org/2022.icon-wlli.5
%P 25-28
Markdown (Informal)
[Word Level Language Identification in Code-mixed Kannada-English Texts using traditional machine learning algorithms](https://aclanthology.org/2022.icon-wlli.5) (Shahiki Tash et al., ICON 2022)
ACL