class_docstr: Phonological transcription `Process` for Latin.
  
  >>> from cltk.core.data_types import Process, Pipeline
  >>> from cltk.tokenizers.processes import LatinTokenizationProcess
  >>> from cltk.text.processes import DefaultPunctuationRemovalProcess
  >>> from cltk.languages.utils import get_lang
  >>> from cltk.languages.example_texts import get_example_text
  >>> from cltk import NLP
  >>> a_pipeline = Pipeline(description="A custom Latin pipeline", processes=[LatinTokenizationProcess, DefaultPunctuationRemovalProcess, LatinPhonologicalTranscriberProcess], language=get_lang("lat"))
  >>> nlp = NLP(language="lat", custom_pipeline=a_pipeline, suppress_banner=True)
  >>> text = get_example_text("lat")
  >>> cltk_doc = nlp.analyze(text)
  >>> [word.phonetic_transcription for word in cltk_doc.words][:5]
  ['[gaɫlɪ̣ja]', '[ɛst̪]', '[ɔmn̪ɪs]', '[d̪ɪwɪsa]', '[ɪn̪]']
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code: def algorithm(self):
      return LatinTranscription()
  
imports: from copy import deepcopy
  from dataclasses import dataclass
  from boltons.cacheutils import cachedproperty
  from cltk.core.data_types import Doc, Process
  from cltk.phonology.ang.phonology import OldEnglishTranscription
  from cltk.phonology.gmh.phonology import MiddleHighGermanTranscription
  from cltk.phonology.got.phonology import GothicTranscription
  from cltk.phonology.grc.phonology import GreekTranscription
  from cltk.phonology.lat.phonology import LatinTranscription
  from cltk.phonology.non.old_swedish.phonology import OldSwedishTranscription
  from cltk.phonology.non.orthophonology import OldNorsePhonologicalTranscriber
label_desc: Use image node_id 1 for calling the LatinPhonologicalTranscriberProcess obj's underlying member method code with example usage: obj.algorithm() and returns: LatinTranscription