code: def _from_list(
      cls,
      split_name: str,
      is_train_split,
      samples: List[Dict],
      cfg: S2TJointDataConfig,
      tgt_dict,
      src_dict,
      pre_tokenizer,
      bpe_tokenizer,
      src_pre_tokenizer,
      src_bpe_tokenizer,
      append_eos,
      use_src_lang_id,
  ) -> SpeechToTextJointDataset:
      audio_root = Path(cfg.audio_root)
      ids = [s[cls.KEY_ID] for s in samples]
      audio_paths = [
          (audio_root / s[cls.KEY_AUDIO]).as_posix() for s in samples
      ]
      n_frames = [int(s[cls.KEY_N_FRAMES]) for s in samples]
      tgt_texts = [s[cls.KEY_TGT_TEXT] for s in samples]
      src_texts = [
          s.get(cls.KEY_SRC_TEXT, cls.DEFAULT_SRC_TEXT) for s in samples
      ]
      speakers = [
          s.get(cls.KEY_SPEAKER, cls.DEFAULT_SPEAKER) for s in samples
      ]
      src_langs = [
          s.get(cls.KEY_SRC_LANG, cls.DEFAULT_LANG) for s in samples
      ]
      tgt_langs = [
          s.get(cls.KEY_TGT_LANG, cls.DEFAULT_LANG) for s in samples
      ]
      tgt_alignment = None
      if cls.KEY_ALIGN in samples[0].keys():
          tgt_alignment = [s[cls.KEY_ALIGN] for s in samples]
      return SpeechToTextJointDataset(
          split_name,
          is_train_split,
          cfg,
          audio_paths,
          n_frames,
          src_texts=src_texts,
          tgt_texts=tgt_texts,
          speakers=speakers,
          src_langs=src_langs,
          tgt_langs=tgt_langs,
          ids=ids,
          tgt_dict=tgt_dict,
          src_dict=src_dict,
          pre_tokenizer=pre_tokenizer,
          bpe_tokenizer=bpe_tokenizer,
          src_pre_tokenizer=src_pre_tokenizer,
          src_bpe_tokenizer=src_bpe_tokenizer,
          append_eos=append_eos,
          alignment=tgt_alignment,
          use_src_lang_id=use_src_lang_id,
      )
  
imports: import logging
  from pathlib import Path
  from typing import Dict, List, NamedTuple, Optional
  import torch
  from fairseq.data import ConcatDataset, Dictionary, ResamplingDataset
  from fairseq.data import data_utils
  from fairseq.data.audio.speech_to_text_dataset import S2TDataConfig, SpeechToTextDataset, SpeechToTextDatasetCreator
label_desc: Use image node_id 1 for calling the SpeechToTextJointDatasetCreator obj's underlying member method code with example usage: obj._from_list(cls, split_name, is_train_split, samples, cfg, tgt_dict, src_dict, pre_tokenizer, bpe_tokenizer, src_pre_tokenizer, src_bpe_tokenizer, append_eos, use_src_lang_id) and returns: SpeechToTextJointDataset