diff --git a/file.wav b/file.wav
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diff --git a/main.py b/main.py
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+++ b/main.py
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+import streamlit as st
+import numpy as np
+import matplotlib.pyplot as plt
+import librosa
+import soundfile as sf
+import wave
+
+
+
+st.set_option('deprecation.showPyplotGlobalUse', False)
+
+with st.sidebar : 
+    p=st.slider("Hearing loss percentage",min_value=0,max_value=100,step=1)
+    p*=0.01
+    filename = "file.wav"
+    f=open(filename,'rb')
+    y,sr = librosa.load(filename)
+    valider = st.button("Valider")
+
+
+if valider:
+    fft_signal = np.fft.fft(y)
+    amp = np.abs(fft_signal)
+    frequencies = np.fft.fftfreq(len(y), 1/sr)
+    a=np.random.choice(len(fft_signal), size=int(len(fft_signal)*p), replace=False)
+    fft_signal[a]=0
+    amp2 = np.abs(fft_signal)
+    y_filtered = np.fft.ifft(fft_signal).real
+    plt.plot(fft_signal)
+    plt.show()
+    y_norm = librosa.util.normalize(y_filtered)
+    sf.write('output_file.wav',y_norm, sr,'PCM_24')
+    audio_file = open('output_file.wav','rb')
+    st.write("Original file")
+    st.audio(f)
+    st.write("Transformed file")
+    st.audio(audio_file)
+    col1,col2=st.columns(2)
+    with col1:
+        st.header('Original audio')
+        fig, ax = plt.subplots()
+        ax.plot(frequencies,amp)
+        st.pyplot(fig)
+    with col2:
+        st.header('Transformed audio')
+        fig2, ax2 = plt.subplots()
+        ax2.plot(frequencies,amp2)
+        st.pyplot(fig2)
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diff --git a/output_file.wav b/output_file.wav
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diff --git a/requirements.txt b/requirements.txt
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+++ b/requirements.txt
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+streamlit==1.29.0
+numpy==1.26.2
+matplotlib==3.8.2
+librosa==0.10.1
+wave==0.0.2
+soundfile==0.12.1
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