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EpitranA library and tool for transliterating orthographic text as IPA (International Phonetic Alphabet). UsageThe Python modules epitran and epitran.vector can be used to easily write more sophisticated Python programs for deploying the Epitran mapping tables, preprocessors, and postprocessors. This is documented below.

Using the epitran Module The Epitran classThe most general functionality in the epitran module is encapsulated in the very simple Epitran class:Epitran(code, preproc=True, postproc=True, ligatures=False, cedictfile=None).Its constructor takes one argument, code, the ISO 639-3 code of the language to be transliterated plus a hyphen plus a four letter code for the script (e.g. 'Latn' for Latin script, 'Cyrl' for Cyrillic script, and 'Arab' for a Perso-Arabic script). It also takes optional keyword arguments:. preproc and postproc enable pre- and post-processors.

These are enabled by default. ligatures enables non-standard IPA ligatures like 'ʤ' and 'ʨ'.

cedictfile gives the path to the dictionary file (relevant only when working with Mandarin Chinese and which, because of licensing restrictions cannot be distributed with Epitran). import epitran epi = epitran.Epitran( 'cmn-Hans ', cedictfile = 'cedict10tsutf-8mdbg.txt ')The most useful public method of the Epitran class is transliterate:Epitran. Transliterate(text, normpunc=False, ligatures=False). Convert text (in Unicode-encoded orthography of the language specified in the constructor) to IPA, which is returned. Normpunc enables punctuation normalization and ligatures enables non-standard IPA ligatures like 'ʤ' and 'ʨ'. Usage is illustrated below (Python 2).

backoff.transliterate( 'हिन्दी ')'ɦindiː ' backoff.translist( 'हिन्दी ') 'ɦ ', 'i ', 'n ', 'd ', 'iː ' backoff.xsampalist( 'हिन्दी ') 'h ', 'i ', 'n ', 'd ', 'i: ' DictFirstThe DictFirst class provides a simple alternative to the Backoff class. Itrequires a dictionary of words known to be of Language A, one word per line in aUTF-8 encoded text file. It accepts three arguments: the language-script codefor Language A, that for Language B, and a path to the dictionary file.

It has one public method, transliteration, which works like Epitran.transliterate except that it returns the transliteration for Language A if the input token is in the dictionary; otherwise, it returns the Language B transliteration of the token. import dictfirst df = dictfirst.DictFirst( 'tpi-Latn ', 'eng-Latn ', './sample-dict.txt ') df.transliterate( 'pela ')'pela ' df.transliterate( 'pelo ')'pɛlow ' Preprocessors, postprocessors, and their pitfallsIn order to build a maintainable orthography to phoneme mapper, it is sometimes necessary to employ preprocessors that make contextual substitutions of symbols before text is passed to a orthography-to-IPA mapping system that preserves relationships between input and output characters. This is particularly true of languages with a poor sound-symbols correspondence (like French and English). Languages like French are particularly good targets for this approach because the pronunciation of a given string of letters is highly predictable even though the individual symbols often do not map neatly into sounds. (Sound-symbol correspondence is so poor in English that effective English G2P systems rely heavily on pronouncing dictionaries.)Preprocessing the inputs words to allow for straightforward grapheme-to-phoneme mappings (as is done in the current version of epitran for some languages) is advantageous because the restricted regular expression language used to write the preprocessing rules is more powerful than the language for the mapping rules and allows the equivalent of many mapping rules to be written with a single rule. Without them, providing epitran support for languages like French and German would not be practical.

However, they do present some problems. Specifically, when using a language with a preprocessor, one must be aware that the input word will not always be identical to the concatenation of the orthographic strings ( orthographicform) output by Epitran.wordtotuples. Instead, the output of wordtotuple will reflect the output of the preprocessor, which may delete, insert, and change letters in order to allow direct orthography-to-phoneme mapping at the next step. The same is true of other methods that rely on Epitran.wordtotuple such as VectorsWithIPASpace.wordtosegs from the epitran.vector module.For information on writing new pre- and post-processors, see the section on ', below.

Using the epitran.vector ModuleThe epitran.vector module is also very simple. It contains one class, VectorsWithIPASpace, including one method of interest, wordtosegs:The constructor for VectorsWithIPASpace takes two arguments:. code: the language-script code for the language to be processed. spaces: the codes for the punctuation/symbol/IPA space in which the characters/segments from the data are expected to reside. The available spaces are listed.Its principle method is wordtosegs:VectorWithIPASpace. Wordtosegs(word, normpunc=False).

Word is a Unicode string. If the keyword argument normpunc is set to True, punctuation discovered in word is normalized to ASCII equivalents.A typical interaction with the VectorsWithIPASpace object via the wordtosegs method is illustrated here (Python 2).

$ tar xjf flite-2.0.0-release.tar.bz2$ cd flite-2.0.0-release/$./configure && make$ sudo make install$ sudo cp bin/t2p /usr/local/binYou should adapt these instructions to local conditions. Installation on Windows is easiest when using Cygwin.

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You will have to use your discretion in deciding where to put t2p.exe on Windows, since this may depend on your python setup. Other platforms are likely workable but have not been tested. LexlookupRecommendedt2p does not behave as expected on letter sequences that are highly infrequent in English. In such cases, t2p gives the pronunciation of the English letters of the name, rather than an attempt at the pronunciation of the name. There is a different binary included in the most recent (pre-release) versions of Flite that behaves better in this regard, but takes some extra effort to install. To install, you need to obtain at least version of Flite.

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We recommend that you obtain the source from GitHub. Untar and compile the source, following the steps below, adjusting where appropriate for your system.