Remove noise detection

app.py

@@ -1,7 +1,10 @@
 import gradio as gr
 import openai
 import threading as th
+import os
 
+os.environ['OPENAI_API_KEY']="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"
+openai.api_key = os.environ['OPENAI_API_KEY']
 
 
 def translateoutput(text,language):
@@ -78,29 +81,11 @@ language_info={
     'Other': 'Other'
 }
         
-import librosa
-import noisereduce as nr
-from pydub import AudioSegment
-
-def enhance_and_denoise_audio(file_path):
-    # Load the audio file
-    data, rate = librosa.load(file_path, sr=None)
-
-    # Perform noise reduction
-    reduced_noise_audio = nr.reduce_noise(y=data, sr=rate)
-
-    # Increase the volume by 10 dB (using PyDub)
-    audio_segment = AudioSegment(reduced_noise_audio.tobytes(), frame_rate=rate, sample_width=reduced_noise_audio.dtype.itemsize, channels=1)
-    enhanced_audio = audio_segment + 10
-
-    # Export the enhanced audio to the same file
-    enhanced_audio.export(file_path, format="wav")
-
-    return file_path        
+   
 
 def translate(audio_file,lan):
     message=""
-    audio_file=enhance_and_denoise_audio(audio_file)
+
     with open(audio_file, 'rb') as f:
         result = openai.Audio.translate("whisper-1", f)
         text=result.text
@@ -117,7 +102,7 @@ def translate(audio_file,lan):
 
 def transcription(audio_file,input_lang):
     global language_info
-    audio_file=enhance_and_denoise_audio(audio_file)
+
     with open(audio_file, 'rb') as f:
         if input_lang=="Other":
             result = openai.Audio.transcribe("whisper-1", f)