Update app.py

app.py

@@ -2,18 +2,25 @@ import gradio as gr
 from transformers import pipeline
 import numpy as np
 
-transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
+transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-tiny.en")
 
-def transcribe(audio):
-    sr, y = audio
+def transcribe(stream, new_chunk):
+    sr, y = new_chunk
     y = y.astype(np.float32)
     y /= np.max(np.abs(y))
 
-    return transcriber({"sampling_rate": sr, "raw": y})["text"]
+    if stream is not None:
+        stream = np.concatenate([stream, y])
+    else:
+        stream = y
+    return stream, transcriber({"sampling_rate": sr, "raw": stream})["text"]
 
 
 demo = gr.Interface(
-    fn=transcribe, inputs=gr.Audio(sources="microphone"), outputs=gr.outputs.Textbox(),
+    transcribe,
+    ["state", gr.Audio(sources=["microphone"], streaming=True)],
+    ["state", "text"],
+    live=True,
 )
 
-demo.launch(debug=True)
+demo.launch()