Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+import soundfile as sf
+from faster_whisper import WhisperModel
+
+model = WhisperModel("tiny.en", device="cpu", compute_type="int8")
+
+def transcribe_audio(audio):
+    sr, data = audio
+    temp_file = "temp.wav"
+    sf.write(temp_file, data, sr, format='wav')
+    segments, info = model.transcribe(temp_file)
+    result = ""
+    for segment in segments:
+        result += "[%.2fs -> %.2fs] %s\n" % (segment.start, segment.end, segment.text)
+    return result
+
+iface = gr.Interface(
+    fn=transcribe_audio,
+    inputs=["microphone"],
+    outputs=gr.Textbox(),
+    title="Team UNDERGOD SIF Hackathon Audio to Text Demo (Using Faster Whisper Tiny int 8 CPU)",
+    description="This Demo Shows our state of the art solution for Psuedo real-time audio transcription (Only English Accepted)"
+)
+
+iface.launch(debug=True)