Voice_Cloning / TTS /vocoder /utils /generic_utils.py
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voice-clone with single audio sample input
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from typing import Dict
import numpy as np
import torch
from matplotlib import pyplot as plt
from TTS.tts.utils.visual import plot_spectrogram
from TTS.utils.audio import AudioProcessor
def interpolate_vocoder_input(scale_factor, spec):
"""Interpolate spectrogram by the scale factor.
It is mainly used to match the sampling rates of
the tts and vocoder models.
Args:
scale_factor (float): scale factor to interpolate the spectrogram
spec (np.array): spectrogram to be interpolated
Returns:
torch.tensor: interpolated spectrogram.
"""
print(" > before interpolation :", spec.shape)
spec = torch.tensor(spec).unsqueeze(0).unsqueeze(0) # pylint: disable=not-callable
spec = torch.nn.functional.interpolate(
spec, scale_factor=scale_factor, recompute_scale_factor=True, mode="bilinear", align_corners=False
).squeeze(0)
print(" > after interpolation :", spec.shape)
return spec
def plot_results(y_hat: torch.tensor, y: torch.tensor, ap: AudioProcessor, name_prefix: str = None) -> Dict:
"""Plot the predicted and the real waveform and their spectrograms.
Args:
y_hat (torch.tensor): Predicted waveform.
y (torch.tensor): Real waveform.
ap (AudioProcessor): Audio processor used to process the waveform.
name_prefix (str, optional): Name prefix used to name the figures. Defaults to None.
Returns:
Dict: output figures keyed by the name of the figures.
""" """Plot vocoder model results"""
if name_prefix is None:
name_prefix = ""
# select an instance from batch
y_hat = y_hat[0].squeeze().detach().cpu().numpy()
y = y[0].squeeze().detach().cpu().numpy()
spec_fake = ap.melspectrogram(y_hat).T
spec_real = ap.melspectrogram(y).T
spec_diff = np.abs(spec_fake - spec_real)
# plot figure and save it
fig_wave = plt.figure()
plt.subplot(2, 1, 1)
plt.plot(y)
plt.title("groundtruth speech")
plt.subplot(2, 1, 2)
plt.plot(y_hat)
plt.title("generated speech")
plt.tight_layout()
plt.close()
figures = {
name_prefix + "spectrogram/fake": plot_spectrogram(spec_fake),
name_prefix + "spectrogram/real": plot_spectrogram(spec_real),
name_prefix + "spectrogram/diff": plot_spectrogram(spec_diff),
name_prefix + "speech_comparison": fig_wave,
}
return figures