Source code for diffsptk.core.b2mc

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# Copyright 2022 SPTK Working Group                                        #
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import numpy as np
import torch
import torch.nn as nn

from ..misc.utils import numpy_to_torch


class MLSADigitalFilterCoefficientsToMelCepstrum(nn.Module):
    """See `this page <https://sp-nitech.github.io/sptk/latest/main/b2mc.html>`_
    for details.

    Parameters
    ----------
    cep_order : int >= 0 [scalar]
        Order of cepstrum, :math:`M`.

    alpha : float [-1 < alpha < 1]
        Frequency warping factor, :math:`\\alpha`.

    """

    def __init__(self, cep_order, alpha):
        super(MLSADigitalFilterCoefficientsToMelCepstrum, self).__init__()

        assert 0 <= cep_order
        assert abs(alpha) < 1

        # Make transform matrix.
        A = np.eye(cep_order + 1)
        np.fill_diagonal(A[:, 1:], alpha)

        self.register_buffer("A", numpy_to_torch(A.T))

    def forward(self, b):
        """Convert MLSA filter coefficients to mel-cepstrum.

        Parameters
        ----------
        b : Tensor [shape=(..., M+1)]
            MLSA filter coefficients.

        Returns
        -------
        mc : Tensor [shape=(..., M+1)]
            Mel-cepstral coefficients.

        Examples
        --------
        >>> b = diffsptk.ramp(4)
        >>> mc2b = diffsptk.MelCepstrumToMLSADigitalFilterCoefficients(4, 0.3)
        >>> b2mc = diffsptk.MLSADigitalFilterCoefficientsToMelCepstrum(4, 0.3)
        >>> b2 = mc2b(b2mc(b))
        >>> b2
        tensor([0.0000, 1.0000, 2.0000, 3.0000, 4.0000])

        """
        mc = torch.matmul(b, self.A)
        return mc