|
7 | 7 |
|
8 | 8 | """ |
9 | 9 |
|
10 | | -# When running this tutorial in Google Colab, install the required packages |
11 | | -# with the following. |
12 | | -# !pip install torchaudio librosa |
13 | | - |
14 | 10 | import torch |
15 | 11 | import torchaudio |
16 | 12 | import torchaudio.transforms as T |
| 13 | +import numpy as np |
17 | 14 |
|
18 | 15 | print(torch.__version__) |
19 | 16 | print(torchaudio.__version__) |
|
23 | 20 | # ----------- |
24 | 21 | # |
25 | 22 |
|
26 | | -import librosa |
27 | 23 | import matplotlib.pyplot as plt |
28 | 24 | from IPython.display import Audio |
29 | 25 | from torchaudio.utils import download_asset |
@@ -98,10 +94,16 @@ def get_spectrogram( |
98 | 94 | ###################################################################### |
99 | 95 | # Visualization |
100 | 96 | # ~~~~~~~~~~~~~ |
| 97 | + |
| 98 | +def power_to_db(S): |
| 99 | + S = np.asarray(S) |
| 100 | + return 10.0 * np.log10(np.maximum(1e-10, S)) |
| 101 | + |
| 102 | + |
101 | 103 | def plot(): |
102 | 104 | def plot_spec(ax, spec, title): |
103 | 105 | ax.set_title(title) |
104 | | - ax.imshow(librosa.amplitude_to_db(spec), origin="lower", aspect="auto") |
| 106 | + ax.imshow(power_to_db(spec**2), origin="lower", aspect="auto") |
105 | 107 |
|
106 | 108 | fig, axes = plt.subplots(3, 1, sharex=True, sharey=True) |
107 | 109 | plot_spec(axes[0], torch.abs(spec_12[0]), title="Stretched x1.2") |
@@ -157,7 +159,7 @@ def preview(spec, rate=16000): |
157 | 159 | def plot(): |
158 | 160 | def plot_spec(ax, spec, title): |
159 | 161 | ax.set_title(title) |
160 | | - ax.imshow(librosa.power_to_db(spec), origin="lower", aspect="auto") |
| 162 | + ax.imshow(power_to_db(spec), origin="lower", aspect="auto") |
161 | 163 |
|
162 | 164 | fig, axes = plt.subplots(3, 1, sharex=True, sharey=True) |
163 | 165 | plot_spec(axes[0], spec[0], title="Original") |
|
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