path=glob.glob('E:/Python_On_All_Dataset/Four emotion_for plot/*.wav')
fig, ax = plt.subplots(nrows=4, ncols=3, sharex=True)
for i in range(4) :
y, sr = librosa.load(path[i], sr=16000)
librosa.display.waveplot(y, sr, ax=ax[i, 0])
mfcc=librosa.feature.mfcc(y)
librosa.display.specshow(mfcc, x_axis='time', ax=ax[i, 1],cmap='viridis')
S = librosa.feature.melspectrogram(y, sr)
librosa.display.specshow(librosa.power_to_db(S), x_axis='time', y_axis='log', ax=ax[i, 2],cmap='viridis')
plt.axis('off')
The result is
