Upload 3 files

app.py

@@ -1,10 +1,12 @@
-from voicefixer.base import VoiceFixer
+from voicefixer import VoiceFixer
 import streamlit as st
 from audio_recorder_streamlit import audio_recorder
 from io import BytesIO
 import soundfile as sf
+# import noisereduce as nr
 
 st.set_page_config(page_title="VoiceFixer app", page_icon=":notes:")
+
 st.title("Voice Fixer App :notes:")
 st.write(
     """
@@ -21,17 +23,26 @@ audio_bytes = audio_recorder(
 )
 try:
     data, samplerate = sf.read(BytesIO(audio_bytes))
-    print(samplerate)
+    #print(samplerate)
     sf.write("original.wav",data,samplerate)
     st.audio(audio_bytes, format = "audio/wav")
     if data.shape[0]>=10000:
+        # reduced_noise = nr.reduce_noise(
+        #     y= (data[:,0]+data[:,1])/2.0,#data[:,0],#, data X,Should be a single channel
+        #     sr=samplerate,
+        #     n_fft=512, #512 recommended for speech, 1024 default
+        #     stationary=False,
+        #     )
+        # st.write("[Classic] Background noise reduction:")
+        # st.audio(reduced_noise, sample_rate=samplerate)
+
         voicefixer.restore(input="original.wav", # low quality .wav/.flac file
-                       output="enhanced_output.wav",
-                       cuda=False, # GPU acceleration
-                       mode=0)
-        st.write("The Audio without background noises and a little enhancement :ocean:")
+                        output="enhanced_output.wav",
+                        cuda=False, # GPU acceleration
+                        mode=0)
+        st.write("[Deep] The Audio without background noises and a little enhancement :ocean:")
         st.audio("enhanced_output.wav")
-
+        
     else: st.warning("Recorded Audio is too short, try again :relieved:")#wink
 except:
     st.info("Try to record some audio :relieved:")

requirements.txt

@@ -8,4 +8,5 @@ progressbar
 torchlibrosa==0.0.7
 GitPython
 streamlit>=1.12.
-pyyaml
+pyyaml
+# noisereduce