This is a GRU-based neural network designed for English word syllabification. The model was trained on data from the Wikimorph dataset.
Use the syllabify()
function from the Syllable
class to syllabify your words:
>>> from eng_syl.syllabify import Syllable >>> syllabler = Syllable() >>> syllabler.syllabify("chomsky") 'chom-sky'
syllabify()
parameters
- text: string- English text to be syllabified. Input should only contain alphabetic characters.
syllabify()
returns the given word with hyphens inserted at syllable boundaries.
The onc_split()
function from the Onceler
class splits single syllables into their constituent Onset, Nucleus, and Coda components.
>>> from eng_syl.onceler import Onceler >>> lorax = Onceler() >>> print(lorax.onc_split("sloan") 'sl-oa-n'
- text: string - English single syllable word/ component to be segmented into Onset, Nucleus, Coda. Input should only contain alphabetic characters.
The ipafy()
function from the on_to_phon
class tries to approximate an IPA pronunciation from a sequence of graphemes.
>>> from eng_syl.phonify import onc_to_phon >>> skibidi = onc_to_phon() >>> print(skibidi.ipafy(['b', 'u', 'tt']) 'bʌt'
- sequence: array of strings - a sequence of English viable onsets, nuclei, and coda