Update app.py

app.py

@@ -110,23 +110,8 @@ custom_css = """
 </style>
 """
 
-
-# Create the Gradio interface
-demo = gr.Interface(
-    fn=predict_dialect,
-    inputs=gr.Audio(),
-    outputs=gr.Label(num_top_classes=5, label="Predicted Dialect"),
-    title="Tamyïz 🍉 Arabic Dialect Identification in Speech",
-        description="""
-            <div class="centered-content">
-                <img src="https://huggingface.co/badrex/mms-300m-arabic-dialect-identifier/resolve/main/assets/logo.png" alt="Logo" style="width: 200px; height: auto; margin-bottom: 20px;">
-                <br>
-                <div>
-                    <p style="font-size: 16px; line-height: 1.6;">
-                    Use this speech model to identify five major Arabic varieties from just a short audio clip.
-                    </p>
-                    <br>
-                    <p style="font-size: 15px; line-height: 1.8;">
+"""
+<p style="font-size: 15px; line-height: 1.8;">
                     <strong>The following Arabic language varieties are supported:</strong>
                     <br><br>
                     ✦ <strong>Modern Standard Arabic (MSA)</strong> - The formal language of media and education
@@ -140,20 +125,33 @@ demo = gr.Interface(
                     ✦ <strong>Maghrebi Arabic</strong> - The distinctive varieties of Morocco, Algeria, Tunisia, and Libya
                     </p>
                     <br>
-                    <p style="font-size: 16px; color: #2563eb;">
-                    Simply <strong>upload an audio file</strong> or <strong>record yourself speaking</strong> to see which dialect you match!
-                    </p>
-                    <p style="font-size: 14px; color: #6b7280;">
-                    Perfect for language learners, linguistics enthusiasts, or anyone curious about Arabic language variation.
-                    </p>
+"""
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=predict_dialect,
+    inputs=gr.Audio(),
+    outputs=gr.Label(num_top_classes=5, label="Predicted Dialect"),
+    title="Tamyïz 🍉 Arabic Dialect Identification in Speech",
+        description="""
+            <div class="centered-content">
+                <img src="https://huggingface.co/badrex/mms-300m-arabic-dialect-identifier/resolve/main/assets/logo.png" alt="Logo" style="width: 200px; height: auto; margin-bottom: 20px;">
+                <br>
+                <div>
+                    <p>
+                    This is a demo for the accurate and robust Transformer-based <a href="https://huggingface.co/badrex/mms-300m-arabic-dialect-identifier" style="color: #FF5349;">model</a> for Spoken Arabic Dialect Identification (ADI). 
+                    From just a short audio clip (5-10 seconds), the model can identify Modern Standard Arabic (<strong>MSA</strong>) as well as four major regional Arabic varieties: Egyptian Arabic, Gulf Arabic, Levantine Arabic, and Maghrebi Arabic. 
+                    
                     <br>
                     <p style="font-size: 13px;">
-                    The demo is based on a Transformer model adapted for the ADI task 
-                    <a href="https://huggingface.co/badrex/mms-300m-arabic-dialect-identifier" style="color: #2563eb;">badrex/mms-300m-arabic-dialect-identifier</a>.
-                    </p>
-                    <p style="font-size: 13px;">
                     Developed with ❤️🤍💚 by <a href="https://badrex.github.io/" style="color: #2563eb;">Badr Alabsi</a>
                     </p>
+
+                    <br>
+                    
+                    <p>
+                    Simply <strong>upload an audio file</strong> or <strong>record yourself speaking</strong> to try out the model!
+                    </p>
                 </div>
             </div>
             """,