EVALUATING AI APPROACHES TO TRANSLATE UZBEK AND KARAKALPAK PAREMIAS INTO ENGLISH

The translation of culturally dense units, such as paremioligical units present significant challenges for machine translation (MT) systems, especially when dealing with under-resourced languages like Uzbek and Karakalpak. Paremioligical units including proverbs, idiomatic expressions, and metaphorical phrases are deeply embedded in the cultural fabric of their source communities. Current AI-driven translation tools often struggle to capture the subtle cultural, historical, and contextual meanings inherent in these expressions. This article evaluates the effectiveness of contemporary MT approaches in rendering Uzbek and Karakalpak paremioligical units into English, highlighting their shortcomings and lead to culturally inadequacy or misleading outputs. Drawing on regionally sourced corpora and scholarly works, it also proposes a hybrid workflow that combines machine-driven efficiency with human cultural and linguistic expertise. By examining diverse strategies and methodologies. This study aims at contributing to the ongoing discourse on improving translation quality and cultural fidelity in the context of under-resourced languages.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-11
DOI
https://doi.org/10.5281/zenodo.14375894
Primary Topic
Natural Language Processing Techniques
Type
article
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article

EVALUATING AI APPROACHES TO TRANSLATE UZBEK AND KARAKALPAK PAREMIAS INTO ENGLISH

Zenodo (CERN European Organization for Nuclear Research)
Natural Language Processing Techniques
article

EVALUATING AI APPROACHES TO TRANSLATE UZBEK AND KARAKALPAK PAREMIAS INTO ENGLISH

article en

Abstract

The translation of culturally dense units, such as paremioligical units present significant challenges for machine translation (MT) systems, especially when dealing with under-resourced languages like Uzbek and Karakalpak. Paremioligical units including proverbs, idiomatic expressions, and metaphorical phrases are deeply embedded in the cultural fabric of their source communities. Current AI-driven translation tools often struggle to capture the subtle cultural, historical, and contextual meanings inherent in these expressions. This article evaluates the effectiveness of contemporary MT approaches in rendering Uzbek and Karakalpak paremioligical units into English, highlighting their shortcomings and lead to culturally inadequacy or misleading outputs. Drawing on regionally sourced corpora and scholarly works, it also proposes a hybrid workflow that combines machine-driven efficiency with human cultural and linguistic expertise. By examining diverse strategies and methodologies. This study aims at contributing to the ongoing discourse on improving translation quality and cultural fidelity in the context of under-resourced languages.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 57%
Natural Language Processing Techniques
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