Update app.py

app.py

@@ -1,26 +1,13 @@
-import whisper
+import whisper  # Ensure 'openai-whisper' is installed
 import gradio as gr
 import subprocess
-from autocorrect import Speller
-from transformers import pipeline
 
 # Load the Whisper model
-model = whisper.load_model("large")
-
-# Initialize autocorrect for Urdu
-spell = Speller(lang='ur')  # Urdu spelling correction
-
-# Load the transformer model for text correction
-corrector = pipeline("text-generation", model="dbmdz/bert-large-uncased-finetuned-urdu")
-
-def correct_urdu_text(text):
-    try:
-        # Use the transformer model to correct the Urdu text
-        corrected_text = corrector(text, max_length=512, num_return_sequences=1)[0]['generated_text']
-        return corrected_text
-    except Exception as e:
-        print(f"Error in text correction: {e}")
-        return text
+try:
+    model = whisper.load_model("large")  # Official Whisper model
+except Exception as e:
+    print(f"Error loading Whisper model: {e}")
+    raise e
 
 def transcribe_video(video_path):
     try:
@@ -33,15 +20,7 @@ def transcribe_video(video_path):
 
         # Transcribe the audio in Urdu
         result = model.transcribe(audio_path, task="transcribe", language="ur")
-        transcribed_text = result["text"]
-
-        # Correct the transcribed text using autocorrect
-        corrected_text = spell(transcribed_text)
-
-        # Apply further correction using transformer-based model
-        final_corrected_text = correct_urdu_text(corrected_text)
-
-        return final_corrected_text
+        return result["text"]
 
     except FileNotFoundError:
         return "Error: ffmpeg is not installed or not found in the environment."
@@ -52,9 +31,9 @@ def transcribe_video(video_path):
 interface = gr.Interface(
     fn=transcribe_video,
     inputs=gr.Video(label="Upload your Urdu-speaking video"),
-    outputs=gr.Textbox(label="Corrected Transcribed Text"),
-    title="Urdu Video Transcription with Correction",
-    description="Upload a video file in Urdu, and this app will transcribe the speech, correct spelling and grammar using Whisper and Transformers.",
+    outputs=gr.Textbox(label="Transcribed Text"),
+    title="Urdu Video Transcription App",
+    description="Upload a video file in Urdu, and this app will transcribe the speech into text using Whisper.",
 )
 
 # Launch the app