Update README.md

README.md

@@ -42,13 +42,14 @@ model-index:
 
 ## Overview
 
-This bandwidth extension model is trained on one specific body conduction sensor data from the [Vibravox dataset](https://huggingface.co/datasets/Cnam-LMSSC/vibravox). 
-The model is designed to to enhance the audio quality of body-conducted captured speech, by denoising and regenerating mid and high frequencies from low frequency content only.
+This bandwidth extension model, trained on [Vibravox](https://huggingface.co/datasets/Cnam-LMSSC/vibravox) body conduction sensor data, enhances body-conducted speech audio by denoising and regenerating mid and high frequencies from low-frequency content.
 
 ## Disclaimer
-This model has been trained for **specific non-conventional speech sensors** and is intended to be used with **in-domain data**.
-Please be advised that using these models outside their intended sensor data may result in suboptimal performance.
+This model, trained for **a specific non-conventional speech sensor**, is intended to be used with **in-domain data**. Using it with other sensor data may lead to suboptimal performance.
 
+## Link to BWE models trained on other body conducted sensors : 
+
+The entry point to all EBEN models for Bandwidth Extension (BWE) is available at [https://huggingface.co/Cnam-LMSSC/vibravox_EBEN_models](https://huggingface.co/Cnam-LMSSC/vibravox_EBEN_models).  
 
 ## Training procedure
 
@@ -70,7 +71,3 @@ audio_16kHz = torchaudio.functional.resample(audio_48kHz, orig_freq=48_000, new_
 cut_audio_16kHz = model.cut_to_valid_length(audio_16kHz)
 enhanced_audio_16kHz = model(cut_audio_16kHz)
 ```
-
-## Link to BWE models trained on other body conducted sensors : 
-
-The entry point to all EBEN models for Bandwidth Extension (BWE) is available at [https://huggingface.co/Cnam-LMSSC/vibravox_EBEN_models](https://huggingface.co/Cnam-LMSSC/vibravox_EBEN_models).