Source code for diffsptk.core.ndps2c

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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 NegativeDerivativeOfPhaseSpectrumToCepstrum(nn.Module):
    """See `this page <https://sp-nitech.github.io/sptk/latest/main/ndps2c.html>`_
    for details.

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

    fft_length : int >= 2 [scalar]
        Number of FFT bins, :math:`L`.

    """

    def __init__(self, cep_order, fft_length):
        super(NegativeDerivativeOfPhaseSpectrumToCepstrum, self).__init__()

        self.cep_order = cep_order
        half_fft_length = fft_length // 2

        assert 0 <= self.cep_order
        assert 2 <= fft_length
        assert self.cep_order <= half_fft_length

        ramp = np.arange(self.cep_order + 1, dtype=np.float64) * half_fft_length
        if self.cep_order == half_fft_length:
            ramp[-1] *= 2
        ramp[1:] = 1 / ramp[1:]
        self.register_buffer("ramp", numpy_to_torch(ramp))

    def forward(self, n):
        """Convert NPDS to cepstrum.

        Parameters
        ----------
        n : Tensor [shape=(..., L/2+1)]
            NDPS.

        Returns
        -------
        c : Tensor [shape=(..., M+1)]
            Cepstrum.

        Examples
        --------
        >>> n = diffsptk.ramp(4)
        >>> ndps2c = diffsptk.NegativeDerivativeOfPhaseSpectrumToCepstrum(4, 8)
        >>> c = ndps2c(n)
        >>> c
        tensor([ 0.0000, -1.7071,  0.0000, -0.0976,  0.0000])

        """
        c = torch.fft.hfft(n)[..., : self.cep_order + 1]
        c = c * self.ramp
        return c