Update README.md

README.md

@@ -1,66 +1,77 @@
+---
 license: cc-by-4.0
 pretty_name: Natural ASR Speech Dataset
-
 tags:
-  - speech
-  - asr
-  - automatic-speech-recognition
-  - hinglish
-  - tamil
-  - bengali
-  - conversational-ai
-  - multilingual
-  - audio-dataset
-
+- speech
+- asr
+- automatic-speech-recognition
+- hinglish
+- tamil
+- bengali
+- conversational-ai
+- multilingual
+- audio-dataset
 task_categories:
-  - automatic-speech-recognition
-
+- automatic-speech-recognition
 size_categories:
-  - n<1K
-
-title: Natural ASR Speech Dataset
-
-description: >
-  This dataset contains natural, spontaneous two-speaker conversations recorded
-  in Hinglish, Tamil, and Bengali, paired with high-quality human-generated
-  transcriptions. The audio captures real conversational flow including fillers,
-  overlaps, informal phrasing, and varied accents, making it ideal for
-  Automatic Speech Recognition (ASR) model training and multilingual
-  conversational AI research.
-
-features:
-  - Two-speaker natural conversations
-  - Hinglish, Tamil, and Bengali coverage
-  - Varied accents, tones, and speaking speeds
-  - Clean manual transcriptions aligned for ASR
-  - Includes fillers, overlaps, and informal dialogue
-  - Suitable for research under CC BY 4.0
-
-intended_uses:
-  direct_use:
-    - Training ASR models
-    - Conversational speech recognition research
-    - Code-mixed language modeling (e.g., Hinglish)
-    - Multilingual and accent-robust ASR systems
-    - Dialogue understanding and speech-to-text evaluation
-    - Benchmarking ASR on spontaneous speech
-  out_of_scope:
-    - Biometric identity recognition
-    - Emotion or psychological profiling
-    - Clinical or medical diagnostic analysis
-    - Deployment without CC BY 4.0 attribution
-    - Real-time mission-critical ASR systems
-
-considerations_and_limitations:
-  - Dataset size is limited (<1,000 samples)
-  - Accent variety exists but does not cover all regions
-  - Natural overlaps, hesitations, and background elements present
-  - Future versions will include more speakers, accents, and languages
-
-license_info:
-  type: CC BY 4.0
-  description: Free to use, modify, distribute, and publish with attribution.
-
-contact:
-  - anoushka@kgen.io
-  - abhishek.vadapalli@kgen.io
+- n<1K
+---
+# Natural ASR Speech Dataset
+
+This dataset contains natural two-person conversations recorded in Hinglish, Tamil, and Bengali, paired with high-quality human-generated transcriptions. The recordings capture spontaneous, real-life dialogue including pauses, fillers, overlaps, and informal phrasing, making it ideal for building robust Automatic Speech Recognition (ASR) systems.
+
+---
+
+## Dataset Features
+
+- Natural, unscripted two-speaker conversations  
+- Hinglish, Tamil, and Bengali multilingual coverage  
+- Varied speaking speeds, tones, and regional accents  
+- Clean and accurate human transcriptions  
+- Includes pauses, interruptions, and conversational flow  
+- Suitable for research and commercial ASR development with attribution  
+
+---
+
+## Intended Uses
+
+### ✅ Direct Use
+
+- Training multilingual and code-mixed ASR models  
+- Benchmarking conversational ASR performance  
+- Hinglish language modeling  
+- Accent-robust ASR system development  
+- Dialogue understanding and speech-to-text tasks  
+- Evaluation of spontaneous-speech ASR accuracy  
+
+### ❌ Out-of-Scope Use
+
+- Speaker or biometric identification  
+- Psychological, emotion, or behavior profiling  
+- Medical or clinical speech analysis  
+- Commercial deployment without CC BY 4.0 credit  
+- Real-time mission-critical ASR applications  
+
+---
+
+## Considerations and Limitations
+
+- ❗ Dataset size is limited (<1,000 samples) and may not include all dialects  
+- 🎧 Contains fillers, hesitations, and overlapping conversation (true natural speech)  
+- 🗣️ Accent diversity exists but is not fully representative of all regions  
+- 🔄 Future versions will add more speakers, languages, and recording environments  
+
+---
+
+## License
+
+**CC BY 4.0** — Free to use, modify, distribute, and publish with attribution.
+
+---
+
+## Contact
+
+For dataset collaboration, contribution, or citation details, contact:
+
+- anoushka@kgen.io  
+- abhishek.vadapalli@kgen.io