Datasets:
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---
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: 8169163578.0
num_examples: 93
download_size: 5351310711
dataset_size: 8169163578.0
---
# 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 | Punjabi | Bhojpuri | Haryanvi |
| 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:
**[arunabh@humynlabs.ai]**
--- |