Data · dataset · 2026
Bangla999-ECD: A Simulated Bengali Emergency Call Transcript Dataset
Listed in Teesside University Research Data Repository
Bangla999-ECD is a simulated Bangla (Bengali) emergency call transcript dataset created to support research in emergency calls and non emergency(or prank) calls classification for Bengali language.
Description
The dataset contains approximately 24,000 text-only call transcripts generated by three native Bengali speakers, covering four categories: Non-emergency, Police, Fire, and Medical emergencies. Each record includes a Bangla transcript of a simulated 999 emergency call, the cleaned version after basic preprocessing, an optional contextual description, a binary emergency indicator(is_emergency), and a multi-class emergency type label.
All samples are synthetic and do not contain real emergency calls, personal identifiers, or sensitive information. The dataset was curated using dataset-level preprocessing steps, including Unicode normalization, punctuation and stopword removal, duplicate elimination using MD5 hashing, and removal of incomplete records. The cleaned dataset is provided in CSV format to facilitate reuse in natural language processing, emergency response research, and Bangla text classification tasks.
Links
Where it is published
- DOI doi.org/10.17632/7k2mxwcc4d.2 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Artificial intelligence · Computer Science & AI · Earth & Environmental Science · Human-computer interaction · Humanities · Machine learning · Natural language processing
- Inferred from text
- Text 75%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/7k2mxwcc4d.2 | 15 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:460208 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Natural Language Processing'] |
| concepts[field].anzsrc:field:460806 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Human-Computer Interaction'] |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:text | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |