Evidence map›Paper›PMID 41210356›Full record

ArticleData in brief2025

BRADS and BRWDS: Multipurpose audio and text datasets for automatic Bangla regional speech recognition.

Umme Aiman, Md Nakibul Islam, Md Hana Sultan Chowdhury, Md Sadekur Rahman, Md Tarek Habib, Mahady Hasan

Abstract read
In one paragraph

Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Umme AimanDepartment of Computer Science and Engineering, Independent University, Bangladesh.
Md Nakibul IslamDepartment of Computer Science and Engineering, Independent University, Bangladesh.
Md Hana Sultan ChowdhuryDepartment of Computer Science and Engineering, Independent University, Bangladesh.
Md Sadekur RahmanDaffodil International University, Bangladesh.
Md Tarek HabibDepartment of Computer Science and Engineering, Independent University, Bangladesh.
Mahady HasanDepartment of Computer Science and Engineering, Independent University, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents an innovative approach to Bangla voice recognition. Although Bangla is the seventh most spoken native language globally, it remains underrepresented in voice recognition research. The dataset contains 298 frequently used Bangla words, including 233 regional words and 65 standard Bangla words. These terms, encompassing various regional pronunciations and meanings, were collected from native speakers in Dhaka, Chattogram, Barisal, Mymensingh, Rajshahi, Sylhet, Rangpur, and Khulna. The 2439 audio segments in the dataset were contributed voluntarily by 85 native speakers and assessed by ten university students. This resource is intended for researchers working on automatic Bangla regional speech recognition systems, with an emphasis on capturing regional pronunciation and linguistic differences. The dataset allows researchers to recreate real-world scenarios during model training by incorporating background noise. Additionally, its modular construction enables further expansion to include new regional words. This multipurpose dataset addresses a critical gap in Bangla speech recognition research and has the potential to drive significant advancements in natural language processing (NLP), particularly with regard to linguistic diversity in Bangladesh.

Indexed as

Automatic speech recognition (ASR)Bangladeshi dialectsBangla regional speech recognitionBengali language processing (BLP)Linguistic diversityNatural language processing (NLP)Real-world speech recognitionRegional pronunciations

Identifiers

PMID41210356
PMCPMC12594939

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.