Update app.py

app.py

@@ -2,25 +2,20 @@ import gradio as gr
 from transformers import pipeline
 import numpy as np
 
-transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-tiny.en")
+transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
 
-def transcribe(stream, new_chunk):
-    sr, y = new_chunk
+def transcribe(audio):
+    sr, y = audio
     y = y.astype(np.float32)
     y /= np.max(np.abs(y))
 
-    if stream is not None:
-        stream = np.concatenate([stream, y])
-    else:
-        stream = y
-    return stream, transcriber({"sampling_rate": sr, "raw": stream})["text"]
+    return transcriber({"sampling_rate": sr, "raw": y})["text"]
 
 
 demo = gr.Interface(
-    fn=transcribe,
-    inputs = gr.Audio(sources=["microphone"], streaming=True),
-    outputs = gr.outputs.Textbox(),
-    live=True,
+    transcribe,
+    gr.Audio(sources=["microphone"]),
+    "text",
 )
 
-demo.launch(debug=True, share=True)
+demo.launch()