N. Ashraf
2022
Overview of CoLI-Kanglish: Word Level Language Identification in Code-mixed Kannada-English Texts at ICON 2022
F. Balouchzahi
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S. Butt
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A. Hegde
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N. Ashraf
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H.l. Shashirekha
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Grigori Sidorov
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Alexander Gelbukh
Proceedings of the 19th International Conference on Natural Language Processing (ICON): Shared Task on Word Level Language Identification in Code-mixed Kannada-English Texts
The task of Language Identification (LI) in text processing refers to automatically identifying the languages used in a text document. LI task is usually been studied at the document level and often in high-resource languages while giving less importance to low-resource languages. However, with the recent advance- ment in technologies, in a multilingual country like India, many low-resource language users post their comments using English and one or more language(s) in the form of code-mixed texts. Combination of Kannada and English is one such code-mixed text of mixing Kannada and English languages at various levels. To address the word level LI in code-mixed text, in CoLI-Kanglish shared task, we have focused on open-sourcing a Kannada-English code-mixed dataset for word level LI of Kannada, English and mixed-language words written in Roman script. The task includes classifying each word in the given text into one of six predefined categories, namely: Kannada (kn), English (en), Kannada-English (kn-en), Name (name), Lo-cation (location), and Other (other). Among the models submitted by all the participants, the best performing model obtained averaged-weighted and averaged-macro F1 scores of 0.86 and 0.62 respectively.
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Co-authors
- F. Balouchzahi 1
- S. Butt 1
- A. Hegde 1
- H. L. Shashirekha 1
- Grigori Sidorov 1
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