Update app.py

app.py

@@ -2,44 +2,37 @@ from transformers import pipeline
 import gradio as gr
 import time
 import unicodedata
-p = pipeline("automatic-speech-recognition",model="kingabzpro/wav2vec2-large-xls-r-300m-Urdu")
 
-def transcribe(audio, state=""):
-    time.sleep(2)
-    text = p(audio)["text"]
-    state += unicodedata.normalize("NFC",text) + " "
-    return state, state
-
-################### Gradio Web APP ################################
-
-title = "Real-Time Urdu ASR"
+p = pipeline("automatic-speech-recognition", model="kingabzpro/wav2vec2-large-xls-r-300m-Urdu")
 
-description = """
-<p>
-<center>
-This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset.
-</center>
-</p>
-<center>
-<img src="https://huggingface.co/spaces/kingabzpro/real-time-Urdu-ASR/resolve/main/Images/cover.jpg" alt="logo" width="550"/>
-</center>
-"""
-
-article = "<p style='text-align: center'><a href='https://dagshub.com/kingabzpro/Urdu-ASR-SOTA' target='_blank'>Source Code on DagsHub</a></p><p style='text-align: center'><a href='https://huggingface.co/blog/fine-tune-xlsr-wav2vec2' target='_blank'>Fine-tuning XLS-R for Multi-Lingual ASR with 🤗 Transformers</a></p></center><center><img src='https://visitor-badge.glitch.me/badge?page_id=kingabzpro/real-time-Urdu-ASR' alt='visitor badge'></center></p>"
+def transcribe(audio):
+    text = p(audio)["text"]
+    transcription = unicodedata.normalize("NFC", text)
+    return transcription
 
+audio_input = gr.inputs.Audio(source="microphone", type="file", label="Upload audio file")
+text_output = gr.outputs.Textbox(label="Transcription")
 
-gr.Interface(
-    fn=transcribe, 
-    inputs=[
-        gr.Audio(source="microphone", type="filepath", streaming=True), 
-        "state"
-    ],
-    outputs=[
-        "textbox",
-        "state"
-    ],
-    title=title,
-    description=description,
-    article=article,
+interface = gr.Interface(
+    fn=transcribe,
+    inputs=audio_input,
+    outputs=text_output,
+    title="Real-Time Urdu ASR",
+    description="""
+    <p>
+    <center>
+    This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset.
+    </center>
+    </p>
+    <center>
+    <img src="https://huggingface.co/spaces/kingabzpro/real-time-Urdu-ASR/resolve/main/Images/cover.jpg" alt="logo" width="550"/>
+    </center>
+    """,
+    article="""
+    <p style='text-align: center'><a href='https://dagshub.com/kingabzpro/Urdu-ASR-SOTA' target='_blank'>Source Code on DagsHub</a></p><p style='text-align: center'><a href='https://huggingface.co/blog/fine-tune-xlsr-wav2vec2' target='_blank'>Fine-tuning XLS-R for Multi-Lingual ASR with 🤗 Transformers</a></p></center><center><img src='https://visitor-badge.glitch.me/badge?page_id=kingabzpro/real-time-Urdu-ASR' alt='visitor badge'></center></p>
+    """,
     theme='EveryPizza/Cartoony-Gradio-Theme',
-    live=True).launch()
+    live=True
+)
+
+interface.launch()