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TTS/vocoder/utils/generic_utils.py

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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