Added HumAwareVAD to VAD Gallery (#194)

docs/turn_taking_gallery.md

@@ -45,6 +45,37 @@ document.querySelectorAll('.tag-button').forEach(button => {
 
 <div class="grid cards" markdown>
 
+-   :speaking_head:{ .lg .middle }:eyes:{ .lg .middle } __HumAware VAD__
+{: data-tags="vad-models"}
+
+    ---
+
+    Description
+    **HumAware-VAD** is a fine-tuned version of **Silero-VAD**, specifically trained to **distinguish humming from actual speech**.
+    Standard VAD models often misclassify humming as speech, leading to inaccurate speech segmentation.
+    **HumAware-VAD** improves detection accuracy in environments with background humming, music, and vocal sounds.  
+
+    **Install Instructions**  
+    ```sh
+    pip install humaware-vad
+    ```  
+    **Use with FastRTC**  
+    ```sh
+    git clone https://github.com/CuriousMonkey7/HumAwareVad.git
+    cd HumAwareVad
+    python app.py
+    ```
+
+    <video width=98% src="https://github.com/user-attachments/assets/ea06a06f-d9e8-4203-a982-56326d160c9e" controls style="text-align: center"></video>  
+
+    [:octicons-arrow-right-24: Demo](https://github.com/CuriousMonkey7/HumAwareVad/blob/main/app.py)  
+
+    [:octicons-code-16: Repository](https://github.com/CuriousMonkey7/HumAwareVad/blob/main/humaware_vad/__init__.py)  
+
+
+</div>
+<div class="grid cards" markdown>
+
 -   :speaking_head:{ .lg .middle }:eyes:{ .lg .middle } __Walkie Talkie__
 {: data-tags="turn-taking-algorithm"}
 
@@ -141,4 +172,4 @@ In this gallery, you can find a collection of turn-taking algorithms and VAD mod
 3. Open a [PR](https://github.com/freddyaboulton/fastrtc/edit/main/docs/turn_taking_gallery.md) to add your model to the gallery! Ideally you model package should be pip installable so other can try it out easily.
 
 !!! tip "Package Naming Convention"
-    It is recommended to name your package `fastrtc-<package-name>` so developers can easily find it on [pypi](https://pypi.org/search/?q=fastrtc-).
+    It is recommended to name your package `fastrtc-<package-name>` so developers can easily find it on [pypi](https://pypi.org/search/?q=fastrtc-).