class_docstr: Audio Processor for TTS.
  
  Note:
      All the class arguments are set to default values to enable a flexible initialization
      of the class with the model config. They are not meaningful for all the arguments.
  
  Args:
      sample_rate (int, optional):
          target audio sampling rate. Defaults to None.
  
      resample (bool, optional):
          enable/disable resampling of the audio clips when the target sampling rate does not match the original sampling rate. Defaults to False.
  
      num_mels (int, optional):
          number of melspectrogram dimensions. Defaults to None.
  
      log_func (int, optional):
          log exponent used for converting spectrogram aplitude to DB.
  
      min_level_db (int, optional):
          minimum db threshold for the computed melspectrograms. Defaults to None.
  
      frame_shift_ms (int, optional):
          milliseconds of frames between STFT columns. Defaults to None.
  
      frame_length_ms (int, optional):
          milliseconds of STFT window length. Defaults to None.
  
      hop_length (int, optional):
          number of frames between STFT columns. Used if ```frame_shift_ms``` is None. Defaults to None.
  
      win_length (int, optional):
          STFT window length. Used if ```frame_length_ms``` is None. Defaults to None.
  
      ref_level_db (int, optional):
          reference DB level to avoid background noise. In general <20DB corresponds to the air noise. Defaults to None.
  
      fft_size (int, optional):
          FFT window size for STFT. Defaults to 1024.
  
      power (int, optional):
          Exponent value applied to the spectrogram before GriffinLim. Defaults to None.
  
      preemphasis (float, optional):
          Preemphasis coefficient. Preemphasis is disabled if == 0.0. Defaults to 0.0.
  
      signal_norm (bool, optional):
          enable/disable signal normalization. Defaults to None.
  
      symmetric_norm (bool, optional):
          enable/disable symmetric normalization. If set True normalization is performed in the range [-k, k] else [0, k], Defaults to None.
  
      max_norm (float, optional):
          ```k``` defining the normalization range. Defaults to None.
  
      mel_fmin (int, optional):
          minimum filter frequency for computing melspectrograms. Defaults to None.
  
      mel_fmax (int, optional):
          maximum filter frequency for computing melspectrograms. Defaults to None.
  
      pitch_fmin (int, optional):
          minimum filter frequency for computing pitch. Defaults to None.
  
      pitch_fmax (int, optional):
          maximum filter frequency for computing pitch. Defaults to None.
  
      spec_gain (int, optional):
          gain applied when converting amplitude to DB. Defaults to 20.
  
      stft_pad_mode (str, optional):
          Padding mode for STFT. Defaults to 'reflect'.
  
      clip_norm (bool, optional):
          enable/disable clipping the our of range values in the normalized audio signal. Defaults to True.
  
      griffin_lim_iters (int, optional):
          Number of GriffinLim iterations. Defaults to None.
  
      do_trim_silence (bool, optional):
          enable/disable silence trimming when loading the audio signal. Defaults to False.
  
      trim_db (int, optional):
          DB threshold used for silence trimming. Defaults to 60.
  
      do_sound_norm (bool, optional):
          enable/disable signal normalization. Defaults to False.
  
      do_amp_to_db_linear (bool, optional):
          enable/disable amplitude to dB conversion of linear spectrograms. Defaults to True.
  
      do_amp_to_db_mel (bool, optional):
          enable/disable amplitude to dB conversion of mel spectrograms. Defaults to True.
  
      do_rms_norm (bool, optional):
          enable/disable RMS volume normalization when loading an audio file. Defaults to False.
  
      db_level (int, optional):
          dB level used for rms normalization. The range is -99 to 0. Defaults to None.
  
      stats_path (str, optional):
          Path to the computed stats file. Defaults to None.
  
      verbose (bool, optional):
          enable/disable logging. Defaults to True.
docstr: Initialize scaler objects used in mean-std normalization.
  
  Args:
      mel_mean (np.ndarray): Mean for melspectrograms.
      mel_std (np.ndarray): STD for melspectrograms.
      linear_mean (np.ndarray): Mean for full scale spectrograms.
      linear_std (np.ndarray): STD for full scale spectrograms.
docstr_tok: ["Initialize","scaler","objects","used","in","mean-std","normalization",".","Args",":","mel_mean","(","np.ndarray",")",":","Mean","for","melspectrograms",".","mel_std","(","np.ndarray",")",":","STD","for","melspectrograms",".","linear_mean","(","np.ndarray",")",":","Mean","for","full","scale","spectrograms",".","linear_std","(","np.ndarray",")",":","STD","for","full","scale","spectrograms","."]
code: def setup_scaler(
      self,
      mel_mean: np.ndarray,
      mel_std: np.ndarray,
      linear_mean: np.ndarray,
      linear_std: np.ndarray,
  ) -> None:
      """Initialize scaler objects used in mean-std normalization.
  
      Args:
          mel_mean (np.ndarray): Mean for melspectrograms.
          mel_std (np.ndarray): STD for melspectrograms.
          linear_mean (np.ndarray): Mean for full scale spectrograms.
          linear_std (np.ndarray): STD for full scale spectrograms.
      """
      self.mel_scaler = StandardScaler()
      self.mel_scaler.set_stats(mel_mean, mel_std)
      self.linear_scaler = StandardScaler()
      self.linear_scaler.set_stats(linear_mean, linear_std)
  
imports: from io import BytesIO
  from typing import Dict, Tuple
  import librosa
  import numpy
  import scipy.io.wavfile
  import scipy.signal
  from TTS.tts.utils.helpers import StandardScaler
  from TTS.utils.audio.numpy_transforms import amp_to_db, build_mel_basis, compute_f0, db_to_amp, deemphasis, find_endpoint, griffin_lim, load_wav, mel_to_spec, millisec_to_length, preemphasis, rms_volume_norm, spec_to_mel, stft, trim_silence, volume_norm
label_desc: Use image node_id 6 for calling the AudioProcessor obj's underlying member method code with example usage: obj.setup_scaler(mel_mean, mel_std, linear_mean, linear_std) without return types