Papers by Priya Rani

3 papers
MHE: Code-Mixed Corpora for Similar Language Identification (2022.lrec-1)

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Challenge: a new corpus of code-mixed data-sets is presented for similar language identification . the data-settings are based on a more-resourced minority language, Magahi .
Approach: They propose a Magahi-Hindi-English code-mixed corpus for similar language identification . they discuss the complexity of the data-set and provide a few baselines .
Outcome: The proposed corpus provides a language id at two levels: word and sentence.
MaCmS: Magahi Code-mixed Dataset for Sentiment Analysis (2024.lrec-main)

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Challenge: Sociolinguists and psychologists have been studying these variations in the lexicons and the language from the 50's . code-mixing is a popular method for understanding people's emotions and attitudes towards various subjects, but low-resourced languages often have a mix of scripts and languages.
Approach: They introduce a new sentiment data, MaCMS, for Magahi-Hindi-English code-mixed language, where Magai is a less-resourced minority language.
Outcome: The proposed dataset is the first Magahi-Hindi-English code-mixed dataset for sentiment analysis tasks.
Weakly-supervised Deep Cognate Detection Framework for Low-Resourced Languages Using Morphological Knowledge of Closely-Related Languages (2023.findings-emnlp)

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Challenge: Existing approaches to cognate detection focus on orthographic, phonetic or contextual models, which under-perform for most under-resourced languages.
Approach: They propose a language-agnostic weakly-supervised deep cognate detection framework for under-resourced languages using morphological knowledge from closely related languages.
Outcome: The proposed framework outperforms state-of-the-art methods on cognate detection datasets across languages and can be extended to a wide range of languages from any language family.

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