# English Syllabifier (eng_syl)
This is a GRU-based neural network designed for English word syllabification. The model was trained on data from the [Wikimorph](https://link.springer.com/chapter/10.1007/978-3-030-78270-2_72) dataset.
## Usage
Use the `syllabify()` function from the `Syllabel` class to syllabify your words:
> >>> from eng_syl.syllabify import Syllabel
> >>> syllabler = Syllabel()
> >>> 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.
## Onceler (Onset, Nucleus, Coda Segmenter)
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.
## Phonify (Grapheme sequence to IPA estimation)
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'])
> 'bÊŒt'
- **sequence**: *array of strings* - sa sequence of English viable onsets, nuclei, and coda
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"description": "\u00ef\u00bb\u00bf# English Syllabifier (eng_syl)\r\nThis is a GRU-based neural network designed for English word syllabification. The model was trained on data from the [Wikimorph](https://link.springer.com/chapter/10.1007/978-3-030-78270-2_72) dataset.\r\n\r\n## Usage\r\n\r\nUse the `syllabify()` function from the `Syllabel` class to syllabify your words:\r\n\r\n> >>> from eng_syl.syllabify import Syllabel\r\n> >>> syllabler = Syllabel()\r\n> >>> syllabler.syllabify(\"chomsky\")\r\n> 'chom-sky'\r\n\r\n`syllabify()` parameters\r\n\r\n - **text**: *string*- English text to be syllabified. Input should only contain alphabetic characters.\r\n\r\n`syllabify()` returns the given word with hyphens inserted at syllable boundaries.\r\n\r\n## Onceler (Onset, Nucleus, Coda Segmenter)\r\n\r\nThe `onc_split()` function from the `Onceler` class splits single syllables into their constituent Onset, Nucleus, and Coda components.\r\n\r\n> >>> from eng_syl.onceler import Onceler\r\n> >>> lorax = Onceler()\r\n> >>> print(lorax.onc_split(\"sloan\")\r\n> 'sl-oa-n'\r\n\r\n - **text**: *string* - English single syllable word/ component to be segmented into Onset, Nucleus, Coda. Input should only contain alphabetic characters.\r\n\r\n## Phonify (Grapheme sequence to IPA estimation)\r\n\r\nThe `ipafy()` function from the `on_to_phon` class tries to approximate an IPA pronunciation from a sequence of graphemes.\r\n\r\n> >>> from eng_syl.phonify import onc_to_phon\r\n> >>> skibidi = onc_to_phon()\r\n> >>> print(skibidi.ipafy(['b', 'u', 'tt'])\r\n> 'b\u00ca\u0152t'\r\n\r\n - **sequence**: *array of strings* - sa sequence of English viable onsets, nuclei, and coda\r\n\r\n",
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