Update app.py

app.py

@@ -1,44 +1,18 @@
 from transformers import pipeline
 import gradio as gr
-import os
-import subprocess
 
 pipe = pipeline(model="tilos/whisper-small-zh-HK")  # change to "your-username/the-name-you-picked"
 
-def video2mp3(video_file, output_ext="mp3"):
-    filename, ext = os.path.splitext(video_file)
-    subprocess.call(["ffmpeg", "-y", "-i", video_file, f"{filename}.{output_ext}"],
-                    stdout=subprocess.DEVNULL,
-                    stderr=subprocess.STDOUT)
-    return f"{filename}.{output_ext}"
-
 def transcribe(audio):
     text = pipe(audio)["text"]
     return text
 
-def video_identity(video):
-    audio_file = video2mp3(video)
-    text = pipe(audio_file)#["text"]
-    print(text)
-    return text
-
-video = gr.Interface(video_identity,
-                    gr.Video(),
-                    "playable_video",
-                    #examples=[
-                    #    os.path.join(os.path.dirname(__file__),
-                    #                 "video/video_sample.mp4")],
-                    cache_examples=True)
-
-voice = gr.Interface(
-    fn=transcribe,
-    inputs=gr.Audio(source="microphone", type="filepath"),
+iface = gr.Interface(
+    fn=transcribe, 
+    inputs=gr.Audio(source="microphone", type="filepath"), 
     outputs="text",
     title="Whisper Small Cantonese",
     description="Realtime demo for Cantonese speech recognition using a fine-tuned Whisper small model.",
 )
 
-
-
-demo = gr.TabbedInterface([video, voice])
-demo.launch()
+iface.launch()