class_docstr: ESPnet speech-to-speech translation model
docstr: Return whether or not vocoder is required.
code: def require_vocoder(self):
      """Return whether or not vocoder is required."""
      return True
  
imports: import logging
  from contextlib import contextmanager
  from typing import Dict, List, Optional, Tuple, Union
  import torch
  from packaging.version import parse
  from typeguard import check_argument_types
  from espnet2.asr.ctc import CTC
  from espnet2.asr.decoder.abs_decoder import AbsDecoder
  from espnet2.asr.encoder.abs_encoder import AbsEncoder
  from espnet2.asr.encoder.conformer_encoder import ConformerEncoder
  from espnet2.asr.encoder.transformer_encoder import TransformerEncoder
  from espnet2.asr.frontend.abs_frontend import AbsFrontend
  from espnet2.asr.postencoder.abs_postencoder import AbsPostEncoder
  from espnet2.asr.preencoder.abs_preencoder import AbsPreEncoder
  from espnet2.asr.specaug.abs_specaug import AbsSpecAug
  from espnet2.layers.abs_normalize import AbsNormalize
  from espnet2.s2st.aux_attention.abs_aux_attention import AbsS2STAuxAttention
  from espnet2.s2st.losses.abs_loss import AbsS2STLoss
  from espnet2.s2st.synthesizer.abs_synthesizer import AbsSynthesizer
  from espnet2.s2st.tgt_feats_extract.abs_tgt_feats_extract import AbsTgtFeatsExtract
  from espnet2.torch_utils.device_funcs import force_gatherable
  from espnet2.train.abs_espnet_model import AbsESPnetModel
  from espnet.nets.e2e_asr_common import ErrorCalculator
  from espnet.nets.e2e_mt_common import ErrorCalculator
  from espnet.nets.pytorch_backend.nets_utils import make_pad_mask, th_accuracy
  from espnet.nets.pytorch_backend.transformer.add_sos_eos import add_sos_eos
label_desc: Use image node_id 11 for calling the ESPnetS2STModel obj's underlying member method code with example usage: obj.require_vocoder() and returns: True