Kathbath Hindi ASR Validation Dataset
Hindi ASR (Automatic Speech Recognition) benchmark validation dataset from Bhashini for supporting the development of robust regional speech recognition systems.
About Dataset
The Kathbath-Hindi-Valid dataset is an essential Hindi ASR benchmark dataset curated to validate Automatic Speech Recognition (ASR) systems under general scenarios. It consists of 1684 hours of labeled speech data, covering 12 Indian languages, offering a diverse and comprehensive resource for researchers and developers. Submitted by Tahir Javed, this dataset plays a crucial role in enhancing the performance and reliability of speech recognition technologies for Hindi and other regional Indian languages.
Dataset Metadata
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
NA
Sector Agnostic
AI4Bharat
Unstructured
NA
NA
N.A.
24/02/25 13:22:50
Open
Hosted
Activity Overview
0
53 
551.04 MB 
883
Tags
- NLP Dataset
- Hindi
- Benchmark
- General Domain
- Automatic Speech Recognition
- Speech Technology
- ASR
- Regional Languages
- Indian Languages
- Multilingual Dataset
- Audio Processing
- Validation Dataset
License Control
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
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Version Control
Version 1(551.04 MB)
- admin·1 year(s) ago
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