api

tokenise(string, strict=False, replace=False, diphthongs=False, tones=False, unknown=False, merge=None) takes an IPA string and returns a list of tokens. A token usually consists of a single letter together with its accompanying diacritics. If two letters are connected by a tie bar, they are also considered a single token. Except for length markers, suprasegmentals are excluded from the output. Whitespace is also ignored. The function accepts the following keyword arguments:

• strict: if set to True, the function ensures that string complies to the IPA spec (the 2015 revision); a ValueError is raised if it does not. If set to False (the default), the role of non-IPA characters is guessed based on their Unicode category (cf. the pitfalls section below).

• replace: if set to True, the function replaces some common substitutes with their IPA-compliant counterparts, e.g. g → ɡ, ɫ → l̴, ʦ → t͡s. Refer to ipatok/data/replacements.tsv for a full list. If both strict and replace are set to True, replacing is done before checking for spec compliance.

• diphthongs: if set to True, the function groups together non-syllabic vowels with their syllabic neighbours (e.g. aɪ̯ would form a single token). If set to False (the default), vowels are not tokenised together unless there is a connecting tie bar (e.g. a͡ɪ).

• tones: if set to True, tone and word accents are included in the output (accent markers as diacritics and Chao letters as separate tokens). If set to False (the default), these are ignored.

• unknown: if set to True, the output includes (as separate tokens) symbols that cannot be classified as letters, diacritics or suprasegmentals (e.g. -, /, $). If set to False (the default), such symbols are ignored. It does not have effect if strict is set to True.

• merge: expects a str, str → bool function to be applied onto each pair of consecutive tokens; those for which the output is True are merged together. You can use this to, e.g., plug in your own diphthong detection algorithm:

  >>> tokenise(string, diphthongs=False, merge=custom_func)
  

tokenize is an alias for tokenise.

>>> tokenise(replace_numbers_with_chao('ɕia⁵¹ɕyɛ²¹⁴'), tones=True)
['ɕ', 'i', 'a', '˥˩', 'ɕ', 'y', 'ɛ', '˨˩˦']

>>> from ipatok import clusterise
>>> clusterise("kiaːltaːʃ")
['k', 'iaː', 'lt', 'aː', 'ʃ']

pitfalls

When strict=True each symbol is looked up in the spec and there is no ambiguity as to how the input should be tokenised.

With strict=False IPA symbols are still handled correctly. A non-IPA symbol would be treated as follows:

• if it is a non-modifier letter (e.g. Γ), it is considered a consonant;

• if it is a modifier (e.g. ˀ) or a combining mark (e.g. ə̇), it is considered a diacritic;

• if it is a modifier tone letter (e.g. ꜍), it is considered a tone symbol;

• if it is neither of those, it is considered an unknown symbol.

Regardless of the value of strict, whitespace characters and underscores are considered to be word boundaries, i.e. there would not be tokens grouping together symbols separated by these characters, even though the latter are not included in the output.

installation

This is a Python 3 package without dependencies and it is offered at the Cheese Shop:

# usually within a virtual environment
pip install ipatok

other IPA packages

• lingpy is a historical linguistics suite that includes an ipa2tokens function.

• loanpy is another historical linguistics suite which works with IPA strings.

• ipapy is a package for working with IPA strings.

• ipalint provides a command-line tool for checking IPA datasets for errors and inconsistencies.

• asjp provides functions for converting between IPA and ASJP.

licence

MIT. Do as you please and praise the snake gods.