"""This module provides phonological/phonetic transcribers for several languages.
**PhonologicalTranscriptionProcess** is the parent-class for all other custom transcription processes.
"""
from copy import copy
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.akk import AkkadianPhonologicalTranscriber
# from cltk.phonology.arb import ArabicPhonologicalTranscriber
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
__author__ = ["Clément Besnier <clem@clementbesnier.fr>"]
[docs]@dataclass
class PhonologicalTranscriptionProcess(Process):
"""General phonological transcription `Process`."""
[docs] def run(self, input_doc: Doc) -> Doc:
transcriber = self.algorithm
output_doc = copy(input_doc)
for word in output_doc.words:
word.phonetic_transcription = transcriber(word.string.lower())
return output_doc
# class AkkadianPhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
# """
# >>> from cltk.core.data_types import Process, Pipeline
# >>> from cltk.tokenizers.processes import AkkadianTokenizationProcess
# >>> from cltk.languages.utils import get_lang
# >>> from cltk.languages.example_texts import get_example_text
# >>> from cltk.nlp import NLP
# >>> pipe = Pipeline(description="A custom Akkadian pipeline", \
# processes=[AkkadianTokenizationProcess, AkkadianPhonologicalTranscriberProcess], \
# language=get_lang("akk"))
# >>> nlp = NLP(language='akk', custom_pipeline=pipe)
# >>> nlp(get_example_text("akk")).phonetic_transcription
#
# """
#
# description = "The default Akkadian transcription process"
#
# @cachedproperty
# def algorithm(self):
# return AkkadianPhonologicalTranscriber()
# class ArabicPhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
# """
# >>> from cltk.core.data_types import Process, Pipeline
# >>> from cltk.tokenizers.processes import ArabicTokenizationProcess
# >>> from cltk.languages.utils import get_lang
# >>> from cltk.languages.example_texts import get_example_text
# >>> from cltk.nlp import NLP
# >>> pipe = Pipeline(description="A custom Old Norse pipeline", \
# processes=[ArabicTokenizationProcess, ArabicPhonologicalTranscriberProcess], \
# language=get_lang("arb"))
# >>> nlp = NLP(language='arb', custom_pipeline=pipe)
# >>> text = get_example_text("arb")
# >>> [word.phonetic_transcription for word in nlp(text)]
#
# """
#
# description = "The default Arabic transcription process"
#
# @cachedproperty
# def algorithm(self):
# return ArabicPhonologicalTranscriber()
[docs]class GothicPhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
"""Phonological transcription `Process` for Gothic.
>>> from cltk.core.data_types import Process, Pipeline
>>> from cltk.tokenizers.processes import OldNorseTokenizationProcess
>>> from cltk.text.processes import DefaultPunctuationRemovalProcess
>>> from cltk.languages.utils import get_lang
>>> from cltk.languages.example_texts import get_example_text
>>> from cltk.nlp import NLP
>>> pipe = Pipeline(description="A custom Gothic pipeline", \
processes=[OldNorseTokenizationProcess, DefaultPunctuationRemovalProcess, \
GothicPhonologicalTranscriberProcess], language=get_lang("got"))
>>> nlp = NLP(language='got', custom_pipeline=pipe, suppress_banner=True)
>>> text = get_example_text("got")
>>> cltk_doc = nlp(text)
>>> [word.phonetic_transcription for word in cltk_doc.words[:5]]
['swa', 'liuhtjɛ', 'liuhaθ', 'jzwar', 'jn']
"""
description = "The default Gothic transcription process"
@cachedproperty
def algorithm(self):
return GothicTranscription()
[docs]class GreekPhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
"""Phonological transcription `Process` for Ancient Greek.
>>> from cltk.core.data_types import Process, Pipeline
>>> from cltk.tokenizers.processes import GreekTokenizationProcess
>>> from cltk.text.processes import DefaultPunctuationRemovalProcess
>>> from cltk.languages.utils import get_lang
>>> from cltk.languages.example_texts import get_example_text
>>> from cltk.nlp import NLP
>>> pipe = Pipeline(description="A custom Greek pipeline", \
processes=[GreekTokenizationProcess, DefaultPunctuationRemovalProcess,\
GreekPhonologicalTranscriberProcess], language=get_lang("grc"))
>>> nlp = NLP(language='grc', custom_pipeline=pipe, suppress_banner=True)
>>> text = get_example_text("grc")
>>> cltk_doc = nlp(text)
>>> [word.phonetic_transcription for word in cltk_doc.words[:5]]
['hó.ti', 'men', 'hy.mệːs', 'ɔ̂ː', 'ɑ́n.dres']
"""
description = "The default Greek transcription process"
@cachedproperty
def algorithm(self):
return GreekTranscription()
[docs]class LatinPhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
"""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]']
"""
description = "The default Latin transcription process"
@cachedproperty
def algorithm(self):
return LatinTranscription()
[docs]class MiddleHighGermanPhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
"""Phonological transcription `Process` for Middle High German.
>>> from cltk.core.data_types import Process, Pipeline
>>> from cltk.tokenizers.processes import MiddleHighGermanTokenizationProcess
>>> from cltk.text.processes import DefaultPunctuationRemovalProcess
>>> from cltk.languages.utils import get_lang
>>> from cltk.languages.example_texts import get_example_text
>>> from cltk.nlp import NLP
>>> pipe = Pipeline(description="A custom Middle High German pipeline", \
processes=[MiddleHighGermanTokenizationProcess, DefaultPunctuationRemovalProcess, \
MiddleHighGermanPhonologicalTranscriberProcess], language=get_lang("gmh"))
>>> nlp = NLP(language='gmh', custom_pipeline=pipe, suppress_banner=True)
>>> text = get_example_text("gmh")
>>> cltk_doc = nlp(text)
>>> [word.phonetic_transcription for word in cltk_doc.words[:5]]
['ʊns', 'ɪst', 'ɪn', 'alten', 'mɛren']
"""
description = "The default Middle High German transcription process"
@cachedproperty
def algorithm(self):
return MiddleHighGermanTranscription()
[docs]class OldEnglishPhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
"""Phonological transcription `Process` for Old English.
>>> from cltk.core.data_types import Process, Pipeline
>>> from cltk.tokenizers.processes import MiddleEnglishTokenizationProcess
>>> from cltk.text.processes import DefaultPunctuationRemovalProcess
>>> from cltk.languages.utils import get_lang
>>> from cltk.languages.example_texts import get_example_text
>>> from cltk.nlp import NLP
>>> pipe = Pipeline(description="A custom Old English pipeline", \
processes=[MiddleEnglishTokenizationProcess, DefaultPunctuationRemovalProcess, \
OldEnglishPhonologicalTranscriberProcess], language=get_lang("ang"))
>>> nlp = NLP(language='ang', custom_pipeline=pipe, suppress_banner=True)
>>> text = get_example_text("ang")
>>> cltk_doc = nlp(text)
>>> [word.phonetic_transcription for word in cltk_doc.words[:5]]
['ʍæt', 'we', 'gɑrˠdenɑ', 'in', 'gæːɑrˠdɑgum']
"""
description = "The default Old English transcription process"
@cachedproperty
def algorithm(self):
return OldEnglishTranscription()
[docs]class OldNorsePhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
"""Phonological transcription `Process` for Old Norse.
>>> from cltk.core.data_types import Process, Pipeline
>>> from cltk.tokenizers.processes import OldNorseTokenizationProcess
>>> from cltk.text.processes import DefaultPunctuationRemovalProcess
>>> from cltk.languages.utils import get_lang
>>> from cltk.languages.example_texts import get_example_text
>>> from cltk.nlp import NLP
>>> pipe = Pipeline(description="A custom Old Norse pipeline", \
processes=[OldNorseTokenizationProcess, DefaultPunctuationRemovalProcess, \
OldNorsePhonologicalTranscriberProcess], language=get_lang("non"))
>>> nlp = NLP(language='non', custom_pipeline=pipe, suppress_banner=True)
>>> text = get_example_text("non")
>>> cltk_doc = nlp(text)
>>> [word.phonetic_transcription for word in cltk_doc.words[:5]]
['gylvi', 'kɔnunɣr', 'reːð', 'θar', 'lœndum']
"""
description = "The default Old Norse poetry process"
@cachedproperty
def algorithm(self):
return OldNorsePhonologicalTranscriber()
[docs]class OldSwedishPhonologicalTranscriberProcess(PhonologicalTranscriptionProcess):
"""Phonological transcription `Process` for Old Swedish.
>>> from cltk.core.data_types import Process, Pipeline
>>> from cltk.tokenizers.processes import OldNorseTokenizationProcess
>>> from cltk.text.processes import DefaultPunctuationRemovalProcess
>>> from cltk.languages.utils import get_lang
>>> from cltk.languages.example_texts import get_example_text
>>> from cltk.nlp import NLP
>>> pipe = Pipeline(description="A custom Old Swedish pipeline", \
processes=[OldNorseTokenizationProcess, DefaultPunctuationRemovalProcess, \
OldSwedishPhonologicalTranscriberProcess], language=get_lang("non"))
>>> nlp = NLP(language='non', custom_pipeline=pipe, suppress_banner=True)
>>> text = "Far man kunu oc dör han för en hun far barn. oc sigher hun oc hænnæ frændær."
>>> cltk_doc = nlp(text)
>>> [word.phonetic_transcription for word in cltk_doc.words[:5]]
['far', 'man', 'kunu', 'ok', 'dør']
"""
description = "The default Old Swedish transcription process"
@cachedproperty
def algorithm(self):
return OldSwedishTranscription()