docstr: Generate a voice from the given audio and text.
  
  Args:
      audio (str): Path to the audio file.
      speaker_id (str): Speaker name.
      voice_dir (str): Path to the directory to save the generate voice.
docstr_tok: ["Generate","a","voice","from","the","given","audio","and","text",".","Args",":","audio","(","str",")",":","Path","to","the","audio","file",".","speaker_id","(","str",")",":","Speaker","name",".","voice_dir","(","str",")",":","Path","to","the","directory","to","save","the","generate","voice","."]
code: def generate_voice(self, audio, speaker_id, voice_dir):
      """Generate a voice from the given audio and text.
  
      Args:
          audio (str): Path to the audio file.
          speaker_id (str): Speaker name.
          voice_dir (str): Path to the directory to save the generate voice.
      """
      if voice_dir is not None:
          voice_dirs = [voice_dir]
          try:
              _ = load_voice(speaker_id, voice_dirs)
          except (KeyError, FileNotFoundError):
              output_path = os.path.join(voice_dir, speaker_id + ".npz")
              os.makedirs(voice_dir, exist_ok=True)
              generate_voice(audio, self, output_path)
  
imports: import os
  from dataclasses import dataclass
  from typing import Optional
  import numpy
  from coqpit import Coqpit
  from encodec import EncodecModel
  from transformers import BertTokenizer
  from TTS.tts.layers.bark.inference_funcs import codec_decode, generate_coarse, generate_fine, generate_text_semantic, generate_voice, load_voice
  from TTS.tts.layers.bark.load_model import load_model
  from TTS.tts.layers.bark.model import GPT
  from TTS.tts.layers.bark.model_fine import FineGPT
  from TTS.tts.models.base_tts import BaseTTS
label_desc: Use image node_id 8 for calling the Bark obj's underlying member method code with example usage: obj.generate_voice(audio, speaker_id, voice_dir) without return types