Update README.md

README.md

@@ -17,23 +17,28 @@ pipeline_tag: text-to-speech
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-Preview-release for Fosdem 2025 with current training epochs (Training is still ongoing)
+> **Preview-release for Fosdem 2025 with current training epochs (Training is still ongoing).**
 
-Demos: https://huggingface.co/spaces/Banafo/Kroko-Streaming-ASR-Wasm (running on CPU in the browser).
-Gradio / python: https://huggingface.co/spaces/Banafo/Kroko-Streaming-ASR-Python
+## Overview
+This is a family of low-latency streaming models designed for use on edge devices.  
+**Goal**: Provide faster or higher-quality performance compared to similarly sized Whisper and other models.
 
+- **Languages**: English, French, German (Spanish and Portuguese planned for release by **Feb 14**).
 
-This is family of low-latency streaming models for use on edge devices.
-Goals:
-- Faster and or higher quality than similar sized Whisper and other models.
+## Demos
+- [**Browser Demo (CPU)**](https://huggingface.co/spaces/Banafo/Kroko-Streaming-ASR-Wasm)  
+  *(Runs entirely in the browser using CPU.)*
+- [**Gradio / Python Demo**](https://huggingface.co/spaces/Banafo/Kroko-Streaming-ASR-Python)
 
-The license is still under consideration (probably Coqui), it will be dual licenced:
-- free for non commercial use
-- Affordable license for commercial use.
+## License
+The license is still under consideration (likely Coqui). The model is intended to be **dual-licensed**:
+- **Free for non-commercial use**.
+- **Affordable license for commercial use**.
 
-English, French, German available. Spanish and Portuguese by 14 feb.
+## Training
+- Training is done with a modified k2/Icefall pipeline.  
+- Inference can be performed with the standard Sherpa project.
 
-Training is done with modified k2/ Icefall. 
-Inference can be done with standard Sherpa project. 
+## Acknowledgements
+Special thanks to the [Lhotse](https://github.com/lhotse-speech/lhotse), [Sherpa](https://github.com/k2-fsa/sherpa), [k2](https://github.com/k2-fsa/k2), and [Icefall](https://github.com/k2-fsa/icefall) teams for their support and tools.
 
-Big thanks and shoutout to the lhotse / Sherpa / k2 / Icefall team.