"""Middle English stress module
"""
import re
from cltk.phonology.enm.syllabifier import (
CONSONANTS,
DIPHTHONGS,
SHORT_VOWELS,
TRIPHTHONGS,
)
from cltk.stem.enm import stem
__author__ = [
"Eleftheria Chatziargyriou <ele.hatzy@gmail.com>",
"Clément Besnier <clem@clementbesnier.fr>",
]
# Soundex replacement rules
dict_SE = {
"p": "1",
"b": "1",
"f": "1",
"v": "1",
"gh": "1",
"sh": "2",
"t": "2",
"d": "2",
"s": "2",
"z": "2",
"r": "2", # TODO
"k": "2",
"g": "2",
"w": "2",
"l": "3",
"m": "4",
"n": "4",
"r": "5", # TODO
}
[docs]class MiddleEnglishStresser:
"""
Middle English stresser
"""
def __init__(self, syllabifier=None):
"""
:param syllabifier: Syllabifier instance
"""
self.syllabifier = syllabifier
[docs] def stress(self, word, stress_rule="FSR") -> list[str]:
"""
:param word: word to stress
:param stress_rule: Stress Rule, valid options:
'FSR': French Stress Rule, stress falls on the ultima, unless it contains schwa (ends with e), in which case the penult is stressed.
'GSR': Germanic Stress Rule, stress falls on the first syllable of the stemm. Note that the accuracy of the function directly depends on that of the stemmer.
'LSR': Latin Stress Rule, stress falls on the penult if its heavy, else, if it has more than two syllables on the antepenult, else on the ultima.
:return: A list containing the separate syllable, where the stressed syllable is prefixed by ' . Monosyllabic words are left unchanged, since stress indicates relative emphasis.
Examples:
>>> from cltk.phonology.syllabify import Syllabifier
>>> from cltk.phonology.enm.syllabifier import DIPHTHONGS, TRIPHTHONGS, SHORT_VOWELS, LONG_VOWELS
>>> enm_syllabifier = Syllabifier()
>>> enm_syllabifier.set_short_vowels(SHORT_VOWELS)
>>> enm_syllabifier.set_vowels(SHORT_VOWELS+LONG_VOWELS)
>>> enm_syllabifier.set_diphthongs(DIPHTHONGS)
>>> enm_syllabifier.set_triphthongs(TRIPHTHONGS)
>>> stresser = MiddleEnglishStresser(enm_syllabifier)
>>> stresser.stress('beren', stress_rule="FSR")
['ber', "'en"]
>>> stresser.stress('prendre', stress_rule="FSR")
["'pren", 'dre']
>>> stresser.stress('yisterday', stress_rule="GSR")
['yi', 'ster', "'day"]
>>> stresser.stress('day', stress_rule="GSR")
['day']
>>> stresser.stress('mervelus', stress_rule="LSR")
["'mer", 'vel', 'us']
>>> stresser.stress('verbum', stress_rule="LSR")
['ver', "'bum"]
"""
assert self.syllabifier is not None
# Syllabify word
syllabified = self.syllabifier.syllabify(word, mode="MOP")
# Check whether word is monosyllabic
if len(syllabified) == 1:
return syllabified
if stress_rule == "FSR":
# Check whether ultima ends in e
if syllabified[-1][-1] == "e":
return (
syllabified[:-2]
+ ["'{0}".format(syllabified[-2])]
+ syllabified[-1:]
)
else:
return syllabified[:-1] + ["'{0}".format(syllabified[-1])]
elif stress_rule == "GSR":
# The word striped of suffixes
st_word = stem(word, strip_suf=False)
affix = word[: len(word) - len(st_word)]
# Syllabify stripped word and affix
syl_word = self.syllabifier.syllabify(st_word, mode="MOP")
# Add stress
syl_word = ["'{0}".format(syl_word[0])] + syl_word[1:]
if affix:
affix = self.syllabifier.syllabify(affix, mode="MOP")
syl_word = affix + syl_word
return syl_word
elif stress_rule == "LSR":
# Check whether penult is heavy (contains more than one mora)
if sum(map(lambda x: x in SHORT_VOWELS, syllabified[-1])) > 1:
return (
syllabified[:-2]
+ ["'{0}".format(syllabified[-2])]
+ syllabified[-1:]
)
elif len(syllabified) > 2:
return (
syllabified[:-3]
+ ["'{0}".format(syllabified[-3])]
+ syllabified[-2:]
)
else:
return syllabified[:-1] + ["'{0}".format(syllabified[-1])]
[docs] def phonetic_indexing(self, word, p="SE") -> str:
"""
:param word: word
:param p: Specifies the phonetic indexing method
SE: Soundex variant for MHG
:return: Encoded string corresponding to the word's phonetic
representation
"""
if p == "SE":
return self._soundex(word)
[docs] def _soundex(self, word):
"""
The Soundex phonetic indexing algorithm adapted to ME phonology.
Algorithm:
Let w the original word and W the resulting one
1) Capitalize the first letter of w and append it to W
2) Apply the following replacement rules
p, b, f, v, gh (non-nasal fricatives) -> 1
t, d, s, sh, z, r, k, g, w (non-nasal alveolars and velars) -> 2
l (alveolar lateral) -> 3
m, n (nasals) -> 4
r (alveolar approximant) -> 5
3) Concetate multiple occurrences of numbers into one
4) Remove non-numerical characters
Notes:
/h/ was thought to be either a voiceless or velar fricative
when occurring in the coda with its most used grapheme being <gh>.
Those phonemes either disappeared, resulting in the lengthening
of preceding vowel clusters, or were developed into /f/ as evident
by modern spelling (e.g. 'enough': /ɪˈnʌf/ and 'though': /ðəʊ/)
Examples:
>>> MiddleEnglishStresser().phonetic_indexing("midel", "SE")
'M230'
>>> MiddleEnglishStresser().phonetic_indexing("myddle", "SE")
'M230'
>>> MiddleEnglishStresser().phonetic_indexing("might", "SE")
'M120'
>>> MiddleEnglishStresser().phonetic_indexing("myghtely", "SE")
'M123'
"""
self.word = word
word = self.word[1:]
for w, val in zip(dict_SE.keys(), dict_SE.values()):
word = word.replace(w, val)
# Remove multiple adjacent occurences of digit
word = re.sub(r"(\d)\1+", r"\1", word)
# Strip remaining letters
word = re.sub(r"[a-zðþƿ]+", "", word)
# Add trailing zeroes and return
return (self.word[0].upper() + word + "0" * 3)[:4]