Apart from the standard Arpabet to IPA conversion rules (https://en.wikipedia.org/wiki/Arpabet), the following ones were observed:
AH is converted to ʌ when bearing primary stress and to ə otherwise (AH1 -> ʌ; AH0, AH2 -> ə) Vowel length is indicated (AA -> ɑː, ER -> ɝː, IY -> iː, UW -> uː). However, unstressed word-final ER and IY are short (i.e., ER0 -> ɝ and IY -> i when word-final).
https://github.com/menelik3/cmudict-ipa
** Change Origial Symbols Tuple like this: **
symbols = {
"a": "ə",
"ey": "eɪ",
"aa": "ɑː",
"ae": "æ",
"ah": "ʌ",
"ao": "ɔ",
"aw": "aʊ",
"ay": "aɪ",
"ch": "ʧ",
"dh": "ð",
"eh": "e",
"er": "ɝː",
"hh": "h",
"ih": "ɪ",
"jh": "ʤ",
"ng": "ŋ",
"ow": "oʊ",
"oy": "ɔɪ",
"sh": "ʃ",
"th": "θ",
"uh": "ʊ",
"uw": "uː",
"zh": "ʒ",
"iy": "iː",
"y": "j"
}
This Python program utilizes the Carnegie-Mellon University Pronouncing Dictionary to convert English text into the [International Phonetic Alphabet](https://en.wikipedia.org/wiki/International_Phonetic_Alphabet).
The `convert` function is used to take English text and convert it to IPA, like so:
```Python
>>> import eng_to_ipa as ipa
>>> ipa.convert("The quick brown fox jumped over the lazy dog.")
'ðə kwɪk braʊn fɑks ʤəmpt ˈoʊvər ðə ˈleɪzi dɔg.'
Note that words that cannot be found in the CMU dictionary are simply reprinted with an asterisk.
-
text : string - The input string of English text to be converted to IPA notation.
-
keep_punct : boolean, optional (default=True) - Determines whether or not the punctuation marks from the input string should be retained or not.
-
retrieve_all : boolean, optional (default=False) - Given that some words might have more than one transcription, this parameter determines whether or not a list of all possible combinations of transcriptions should be returned (True) or just the string of one transcription (False).
-
stress_marks : string, optional (default='both') - Determines whether or not the primary and secondary stress markings (ˈ, ˌ) should be retained. Understood arguments are:
- "primary" - retains primary stress only
- "secondary" - retains secondary stress only
- "both" - to keep both primary and secondary stress markers.
-
mode : string, optional (default='sql') - Accepts "sql" or "json", depending on which version of the database you'd like to use. As another option for JSON users, simply use the function
jonvert
instead ofconvert
.
The ipa_list
function returns a list of each word as a list of all its possible transcriptions. It has all the same
optional stress_marks
and keep_punct
parameters as convert
.
>>> ipa.ipa_list("The record was expensive.")
[['ði', 'ðə'], ['rəˈkɔrd', 'rɪˈkɔrd', 'ˈrɛkərd'], ['wɑz'], ['ɪkˈspɛnsɪv.']]
The isin_cmu
function takes a word (or list of words) and checks if it is in the CMU pronouncing dictionary (returns
True
or False
). If a list of words is provided, then True
will only be returned if every provided word is in the dictionary.
>>> ipa.isin_cmu("The dentist opened a new practice.")
True
>>> ipa.isin_cmu("emoji")
False
The get_rhymes
function returns a list of rhymes for a word or set of words.
>>> ipa.get_rhymes("rhyming function")
[['climbing', 'diming', 'liming', 'priming', 'timing'], ['compunction', 'conjunction', 'dysfunction', 'injunction', 'junction', 'malfunction']]
Use the jhymes
function instead to force usage of the JSON database.
The syllable_count
function returns an integer, corresponding to the number of syllables in a word. Returns a list of
syllable counts if more than one word is provided in the input string.
>>> ipa.syllable_count("computer programming")
[3, 3]
For another Python package that offers support for rhyming and syllable counts (as well as other cool things), see pronouncingpy.
Note: I'd like to make this project easily available/installable from pip, but I don't know how. Looking for help!