Update README.md

README.md

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----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+task_categories:
+- automatic-speech-recognition
+tags:
+- audio
+- indic
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: 
+    - "Metadata.csv"
+    - "*.wav"
+dataset_info:
+  features:
+    - name: file_name
+      dtype: audio
+    - name: language
+      dtype: string
+  splits:
+    - name: train
+---
+# 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]**
+
+---