A Bengali-Hindi-Telugu parallel corpus for enhanced literary machine translation

. The development process of BHT25 followed structured data cleaning, preprocessing, sentence alignment, and human validation procedures. Each sentence triplet is assigned a unique identifier to ensure traceability and a systematic analysis. The dataset is released under the CC-BY-4.0 license on Hugging Face, along with preprocessing scripts and documentation, to support research on Indic machine translation and multilingual literary processing. An extended version, annotated with four emotion labels (joy, sadness, anger, fear) and pairwise semantic similarity scores, is also included to support future research on emotion-aware translation and semantic consistency.

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Publication Details

Journal
Data in Brief
Published
2026-04-14
DOI
https://doi.org/10.1016/j.dib.2026.112775
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

A Bengali-Hindi-Telugu parallel corpus for enhanced literary machine translation

Aruna Priya, Anik Nandi, Suryakanth V. Gangashetty, Sudeshna Sani et al.
Data in Brief
Natural Language Processing Techniques
article

A Bengali-Hindi-Telugu parallel corpus for enhanced literary machine translation

Aruna Priya, Anik Nandi, Suryakanth V. Gangashetty, Sudeshna Sani, Akhilesh Kumar Dubey, Vineeth Kumar, Samudravijaya K
article en

Abstract

. The development process of BHT25 followed structured data cleaning, preprocessing, sentence alignment, and human validation procedures. Each sentence triplet is assigned a unique identifier to ensure traceability and a systematic analysis. The dataset is released under the CC-BY-4.0 license on Hugging Face, along with preprocessing scripts and documentation, to support research on Indic machine translation and multilingual literary processing. An extended version, annotated with four emotion labels (joy, sadness, anger, fear) and pairwise semantic similarity scores, is also included to support future research on emotion-aware translation and semantic consistency.

Data in BriefVol. 66
Woxsen School of Business (IN), ICFAI Foundation for Higher Education (IN), Koneru Lakshmaiah Education Foundation (IN)
Ministry of Electronics and Information technology
Quality Education
Openalex Percentile: Top 23%
Natural Language Processing Techniques
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A Bengali-Hindi-Telugu parallel corpus for enhanced literary machine translation — Aruna Priya, Anik Nandi, et al. · Data in Brief (2026) | TGRS Research Map | TGRS