Datasets:
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
tags:
- audio
- indic
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: audio
dtype: audio
- name: file_name
dtype: string
- name: language
dtype: string
splits:
- name: train
num_bytes: 8169163578
num_examples: 93
download_size: 5351310711
dataset_size: 8169163578
Indic Conversational ASR Dataset
📌 Dataset Overview
This dataset contains high-quality audio samples curated for Automatic Speech Recognition (ASR) tasks.
The recordings are optimized for speech recognition and are provided with:
- Sampling Rate: 16 kHz – 24 kHz
- Bit Depth: 16-bit
- Audio Type: Non-scripted conversational speech
- Format: Dual-speaker conversations
🌏 Supported Languages & Variants
| Telugu | Kannada | Malayalam | Bengali (IN – Kolkata) | Bengali (IN – Non-Kolkata) |
| Bengali (BD) | Assamese | Odia | Gujarati | Marathi |
| Tamil | Tamilish | Hinglish | Marvadi | Chhattisgarhi |
👥 Speaker Representation
- Dual-speaker conversational recordings
- Natural, spontaneous speech
- Female speaker representation: ~20%–30%
🛠 Dataset Creation Methodology
📥 Data Collection
Speech data was collected through micro-communities across India and neighboring regions, spanning:
- Tier 1 cities
- Tier 2 cities
- Tier 3 cities
This approach ensured:
- Linguistic diversity
- Regional accent coverage
- Authentic conversational patterns
🎙 Recording Setup
- Non-scripted, dual-speaker conversations
- Duration: 10–30 minutes per recording
- Topics include:
- Business
- Finance
- Politics
- Daily-life discussions
✅ Quality Validation
All audio samples underwent automated and manual validation.
🔍 Automated Checks
SRMR • SIGMOS • VQScore • WVMOS
Evaluated: Signal quality, perceptual clarity, speech intelligibility.
👥 Human Review
Ensured conversational naturalness, audio clarity, and ASR suitability.
🎯 Dataset Intended Purpose
✔️ Intended Uses
This dataset is designed for:
- Training and fine-tuning Automatic Speech Recognition (ASR) models
- Benchmarking conversational ASR systems
- Code-mixed speech recognition research
- Speaker turn detection and interruption modeling
- Informal and spontaneous speech modeling
- Emotion recognition research
- Speaker interaction analysis
- Conversational AI research
- Academic and open-source research for low-resource Indic languages
🚫 Out-of-Scope Uses
This dataset is not intended for:
- Real-time, safety-critical, or production-grade systems without additional validation
- Commercial deployment without proper attribution and compliance with CC BY 4.0
- Medical, clinical, legal, or diagnostic decision-making applications
📜 License
This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
📬 Contact
For queries regarding this dataset, please reach out to: