Create app.py

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from transformers import pipeline
+import os
+
+
+pipe = pipeline(task="automatic-speech-recognition", model="geokanaan/Whisper_Base_Lebanese_Arabizi")
+
+
+
+def transcribe(audio, actual_transcription):
+    text = pipe(audio)
+    return text['text']
+
+
+HF_TOKEN = os.getenv('WRITE')
+hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "flagged_Audio_Lebanese")
+
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=[
+        gr.Audio(sources="microphone", type="filepath"),
+        gr.Textbox(label="Actual Transcription", optional=True)  
+    ],
+    outputs="text",
+    title="arabeasy",
+    description="Realtime demo for Lebanese Arabizi speech recognition",
+    allow_flagging='manual',  
+    flagging_callback=hf_writer
+)