pyclts

Tooling to access and curate CLTS data.

CLTS is an attempt to create a system that allows to translate and compare different phonetic transcription systems and pyclts provides a Python API to data and comparison functionality.

Install

pyclts provides a Python API for CLTS data. Using pyclts requires this data to be available locally, either as repository clone, or as unzipped download of a released version.

To install pyclts run

pip install pyclts

This will install the python API as well as a command line tool clts. Both, require the location of the data as argument:

>>> from pyclts import CLTS
>>> clts = CLTS('PATH/TO/clts')

or

clts --repos PATH/TO/clts stats

To save this effort, the data location can also be looked up in a cldfcatalog config file, under the key clts.

Such a config file (and the repository clone) can be created automatically, by installing cldfbench and running cldfbench catconfig (please note that command depends on the pyglottolog and pyconcepticon libraries).

Compatibility

Note that the CLTS data release and the pyclts version must be compatible.

• pyclts < 3.0 works with CLTS data up to version 1.4.1
• pyclts >= 3.0 works with CLTS data >= 2.0

Overview

Using pyclts is exemplified in this short code snippet:

>>> from pyclts import CLTS
>>> clts = CLTS('clts/')
>>> asjp = clts.transcriptionsystem('asjpcode')
>>> snd1 = clts.bipa['ts']
>>> snd2 = asjp['c']
>>> snd1.name
'voiceless alveolar sibilant affricate consonant'
>>> snd2.name
'voiceless alveolar sibilant affricate consonant'
>>> clts.bipa.translate('ts a ŋ ə', asjp)
'c E N 3'
>>> asjp.translate('C a y', clts.bipa)
'tʃ ɐ j'

Notes:

• Since "bipa" is the standard transcriptionsystem in CLTS, it's available - as shortcut - directly as bipa attribute of CLTS.
• We represent the sounds ts and c, depending on the alphabet from which they are taken.

Sounds

pyclts can not only deal with sound that are already in our database. Intead, We it tries to create "unknown" sounds automatically and infer its features from the set of diacritics and the base sound:

>>> sound = clts.bipa['dʱʷ']
>>> sound.name
'labialized breathy voiced alveolar stop consonant'
>>> sound.generated
True
>>> sound.alias
True
>>> print(sound)
dʷʱ
>>> print(sound.uname)
LATIN SMALL LETTER D / MODIFIER LETTER SMALL W / MODIFIER LETTER SMALL H WITH HOOK
>>> print(sound.codepoints)
U+0064 U+02b7 U+02b1

You can see, since we represent breathy-voice phonation differently, we flag this sound as an alias. Also since it is not yet in our database explicitly coded, we flag it as a "generated" sound. In a similar way, you can generate sounds from their names:

>>> sound = clts.bipa['pre-aspirated voiced aspirated bilabial stop consonant']
>>> print(sound)
ʰbʰ
>>> sound.generated
True
>>> sound.name
'pre-aspirated aspirated voiced bilabial stop consonant'

Note that this sound probably does not exist in any language, but we generate it from the feature components. Note also that the name that is automatically given for the sound automatically orders how the features are put together to form the sound identifier. In principle, our features bundles are unordered, but we try to decide for some explicit order of features to enhance comparison.

Transcription systems and sound classes

You can also use our transcription data to convert from one transcription system to a given dataset (note that backwards-conversion may not be possible, as transcription data is often limited):

>>> sca = clts.soundclass('sca')
>>> clts.bipa.translate('f a: t ə r', sca)
'B A T E R'

The translation can also be done by loading the transcription data directly:

>>> sca('v a t ə r')
['B', 'A', 'T', 'E', 'R']

Basic Structure of the Package

pyclts provides access to three basic types of data:

• transcription systems (pyclts.transcriptionsystems.TranscriptionSystem), a system that can generate sounds
• transcription data (pyclts.transcriptiondata.TranscriptionData): a dataset with a fixed number of sounds
• sound classes (pyclts.soundclasses.SoundClasses): a dataset with a direct mapping from sounds to a concrete character (the sound class)

Transcription data is linked to our transcription system by the grapheme for the B(road) IPA transcription system, which serves as our default, and the name, which follows the IPA conventions with some modifications which were needed to make sure that we can represent sounds that we regularly find in cross-linguistic datasets.

Parsing Procedure