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import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import torchaudio
import numpy as np
import pdb
test_token = [{'word': 'MANY', 'start_time': 1.3, 'end_time': 1.5}, {'word': 'COMPLICATED', 'start_time': 1.56, 'end_time': 2.14}, {'word': 'IDEAS', 'start_time': 2.24, 'end_time': 2.56}, {'word': 'ABOUT', 'start_time': 2.66, 'end_time': 2.9}, {'word': 'THE', 'start_time': 3.0, 'end_time': 3.06}, {'word': 'RAINBOW', 'start_time': 3.14, 'end_time': 3.42}, {'word': 'HAVE', 'start_time': 3.48, 'end_time': 3.58}, {'word': 'BEEN', 'start_time': 3.62, 'end_time': 3.74}, {'word': 'FORMED', 'start_time': 3.84, 'end_time': 4.16}]
laronix_green = [120, 189, 145]
def token_plot(audio, sr, token):
# pdb.set_trace()
# Get X axis
duration = audio.squeeze().shape[0] / sr
x = np.arange(0, duration, 1/sr)
# Wave plot
fig, ax = plt.subplots(figsize=(20, 4))
ax.plot(x, audio.squeeze(), color="#78bd91")
ax.set_xlabel("Time / s")
ax.set_ylabel("Amplitude")
y_limit = np.max(audio.numpy())
# pdb.set_trace()
# load token
for i in token:
word, start_time, end_time = i.values()
# plot tokens
ax.text(x=start_time, y=y_limit, s=word, ha="left", fontsize="large", fontstretch="ultra-condensed")
# plot token boundarys
ax.vlines(x=start_time, ymin=np.min(audio.numpy()), ymax=y_limit, colors="black")
# ax.vlines(x=end_time, ymin=np.min(audio.numpy()), ymax=y_limit, colors="red")
plt.tight_layout()
# pdb.set_trace()
# fig.savefig("1.png")
return fig
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