In [1]:

    

import librosa
import librosa.display
import IPython.display
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.style as ms

ms.use('seaborn-muted')
%matplotlib inline


    

In [2]:

    

file_path = "../data/songData/genres/blues/blues.00000.wav"
y, sr = librosa.load(file_path)

IPython.display.Audio(data=y, rate=sr)


    

    
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In [3]:

    

# separete harmonic and percussive
y_h, y_p = librosa.effects.hpss(y)
IPython.display.Audio(data=y_h, rate=sr)


    

    
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In [4]:

    

# Listen the percussive part
IPython.display.Audio(data=y_p, rate=sr)


    

    
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In [5]:

    

# shifting pitch
y_shift = librosa.effects.pitch_shift(y, sr, 7)
IPython.display.Audio(data=y_shift, rate=sr)


    

    
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In [6]:

    

# tempo change 
y_slow = librosa.effects.time_stretch(y, 0.5)
IPython.display.Audio(data=y_slow, rate=sr)


    

    
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In [11]:

    

mfcc_effect = librosa.effects.feature.mfcc(y, sr=sr, n_mfcc=13)

plt.figure(figsize=(12, 6))
librosa.display.specshow(mfcc_effect)
plt.colorbar()
plt.tight_layout()