small update

README.md

@@ -1,5 +1,5 @@
 ---
-title: Rnnt Whisper Encoder
+title: Vietnamese Streaming RNN-T 
 emoji: 💻
 colorFrom: yellow
 colorTo: red
@@ -8,7 +8,7 @@ sdk_version: 5.17.1
 app_file: app.py
 pinned: false
 license: apache-2.0
-short_description: RNN-T Whisper Encoder
+short_description: RNN-T with Whisper Encoder
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -101,12 +101,12 @@ def process_uploaded_file(
         MyPrint(str(e))
         return "", build_html_output(str(e), "result_item_error")
 
-title = "# Streaming RNN-T with Whisper Encoder"
+title = "# Vietnamese Streaming RNN-T"
 description = """
-Visit <https://github.com/HKAB/rnnt-whisper-tutorial/> for more information.
+Visit <https://github.com/HKAB/vietnamese-rnnt-tutorial/> for more information.
 
-- This model runs on CPU (Free tier) so the RTF of FP32 model is around 1.5.
-- This model mights not work with your microphone since it was trained on a quite clean dataset. Try to speak loudly and clearly 😃
+- This model runs on a very slow CPU (it's Free tier) so the RTF of FP32 model is around 1.5.
+- This model mights not work with your microphone since it was trained on a quite clean dataset. Try to speak loudly 😃
 - Although you upload a full audio file, the model will process it in a streaming fashion.
 """
 
@@ -278,17 +278,6 @@ with demo:
             recorded_output = gr.Textbox(label="Recognized speech from recordings")
             recorded_html_info = gr.HTML(label="Info")
 
-            gr.Examples(
-                examples=examples,
-                inputs=[
-                    microphone,
-                    model_type
-                ],
-                outputs=[recorded_output, recorded_html_info],
-                fn=process_microphone,
-                label="Cherry-picked examples",
-            )
-
         upload_button.click(
             process_uploaded_file,
             inputs=[