code: def _get_dct_matrix(num_ceps: int, num_mel_bins: int) -> Tensor:
      # returns a dct matrix of size (num_mel_bins, num_ceps)
      # size (num_mel_bins, num_mel_bins)
      dct_matrix = torchaudio.functional.create_dct(
          num_mel_bins, num_mel_bins, "ortho"
      )
      # kaldi expects the first cepstral to be weighted sum of factor sqrt(1/num_mel_bins)
      # this would be the first column in the dct_matrix for torchaudio as it expects a
      # right multiply (which would be the first column of the kaldi's dct_matrix as kaldi
      # expects a left multiply e.g. dct_matrix * vector).
      dct_matrix[:, 0] = math.sqrt(1 / float(num_mel_bins))
      dct_matrix = dct_matrix[:, :num_ceps]
      return dct_matrix
  
imports: import math
  from typing import Tuple
  import torch
  import torchaudio
  from torch import Tensor
label_desc: Use image node_id 18 for calling a global function with example usage: _get_dct_matrix(num_ceps, num_mel_bins) and returns: dct_matrix