Bengali Noisy ASR Benchmark Dataset: Kathbath Bengali Noisy test unknown
Bengali ASR (Automatic Speech Recognition) Benchmark noisy test dataset from Bhashini for supporting the development of robust regional speech recognition systems.
About Dataset
The Kathbath-Bengali-Noisy-Test-Unknown dataset is a comprehensive benchmark for evaluating Automatic Speech Recognition (ASR) systems in noisy conditions for the Bengali language. Featuring 1684 hours of labeled speech data across 12 Indian languages, it is specifically designed to test ASR models under challenging acoustic scenarios in general domains. Submitted by Tahir Javed, this dataset is an essential resource for advancing ASR technologies for Bengali and other regional Indian languages, enabling robust multilingual ASR systems capable of handling noise.
Dataset Metadata
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
NA
Sector Agnostic
AI4Bharat
Unstructured
NA
NA
N.A.
24/02/25 13:23:30
Open
Hosted
Activity Overview
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244.92 MB
Tags
- Bengali
- NLP Dataset
- Benchmark
- General Domain
- Automatic Speech Recognition
- Speech Technology
- ASR
- Regional Languages
- Indian Languages
- Multilingual Dataset
- Audio Processing
- Noisy
License Control
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
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Version Control
Version 1(244.92 MB)
- admin·1 year(s) ago
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