class_docstr: Time invariant MLSA filter.
  
  This module is used to perform noise shaping described in
  `An investigation of noise shaping with perceptual
   weighting for WaveNet-based speech generation`_.
  
  Args:
      coef (ndaaray): MLSA filter coefficient (D,).
      alpha (float): All pass constant value.
      n_shift (int): Shift length in points.
  
  .. _`An investigation of noise shaping with perceptual
      weighting for WaveNet-based speech generation`:
      https://ieeexplore.ieee.org/abstract/document/8461332
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docstr: Apply time invariant MLSA filter.
  
  Args:
      y (ndarray): Waveform signal normalized from -1 to 1 (N,).
  
  Returns:
      y (ndarray): Filtered waveform signal normalized from -1 to 1 (N,).
docstr_tok: ["Apply","time","invariant","MLSA","filter",".","Args",":","y","(","ndarray",")",":","Waveform","signal","normalized","from","-1","to","1","(","N",",",")",".","Returns",":","y","(","ndarray",")",":","Filtered","waveform","signal","normalized","from","-1","to","1","(","N",",",")","."]
code: def __call__(self, y):
      """Apply time invariant MLSA filter.
  
      Args:
          y (ndarray): Waveform signal normalized from -1 to 1 (N,).
  
      Returns:
          y (ndarray): Filtered waveform signal normalized from -1 to 1 (N,).
  
      """
      # check shape and type
      assert len(y.shape) == 1
      y = np.float64(y)
  
      # get frame number and then replicate mlsa coef
      num_frames = int(len(y) / self.n_shift) + 1
      coef = np.tile(self.coef, [num_frames, 1])
  
      return self.mlsa_filter.synthesis(y, coef)
  
file_path: espnet/utils/generate_wav_from_fbank.py
imports: import argparse
  import logging
  import os
  import time
  import h5py
  import numpy
  import pysptk
  import torch
  from scipy.io.wavfile import write
  from sklearn.preprocessing import StandardScaler
  from espnet.nets.pytorch_backend.wavenet import WaveNet, decode_mu_law, encode_mu_law
  from espnet.utils.cli_readers import file_reader_helper
  from espnet.utils.cli_utils import get_commandline_args
label_desc: Use image node_id 2 for calling the TimeInvariantMLSAFilter obj's underlying member method code with example usage: obj.__call__(y) and returns: self