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Python

# Read WAV and MP3 files to array
from pydub import AudioSegment
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
#from scipy.io import wavfile
#from plotly.offline import init_notebook_mode
#import plotly.graph_objs as go
#import plotly
import sklearn
import IPython
from IPython.display import Image
import librosa
import librosa.display
#import eli5
#import logguru
import os
import warnings
warnings.filterwarnings('ignore')
path=os.path.dirname(__file__)
os.chdir(path)
sampleFolder = os.path.join(path, 'AudioSamples')
sampleList = os.listdir(sampleFolder)
for sample_fileName in sampleList:
print(sample_fileName)
#print(sampleList[0])
filepath = os.path.join(sampleFolder,sample_fileName)
#filepath = os.path.join(sampleFolder,sampleList[0])
y,sr = librosa.load(filepath,duration=2.97)
ps = librosa.feature.melspectrogram(y=y, sr=sr)
#print(ps.shape)
#print(ps)
#print(y)
##verschiedene spectral anzeigen
#librosa.display.specshow(ps,y_axis='mel',x_axis='time')
#librosa.display.waveplot(ps, sr=sr)
X = librosa.stft(y)
Xdb = librosa.amplitude_to_db(abs(X))
plt.figure(figsize=(14,5))
librosa.display.specshow(Xdb,sr=sr,x_axis='time',y_axis='hz')
plt.show()