Feature-Based Alignment Analyses with LingPy and CLTS (2)
Requirements (can all be installed with PIP)
This is a short patch for LingPy's Waterman-Eggert implementation and an illustration how the algorithm can be used to carry out the alignment of two sentences provided in phonetic transcription in linguistics. To test this script, make sure to install LingPy and run the following in your terminal:
$ python code.py
|Bodth-2019-664-5||5||3sg||262||HE OR SHE OR IT|
|Bodth-2019-664-7||7||above, top||2379||UP OR ABOVE|
To run the script provided here, make sure to download the GIST, and install the requirements for LingRex. Then, simply type:
$ python code.py
To run the script provided here, make sure to download the data from Zenodo, and unpack the folder
cd into the folder, and run the script as follows:
$ python to_wordlist.py
To install all requirements, just type:
This little repository contains the analyses I have done to test the Morfessor software on sparse data. It should be mentioned that I just used the defaults for the computation, so it is quite possible, that the results could be further enhanced.
To install Morfessor, just type:
$ pip install morfessor
This GIST accompanies the blogpost explaining the code, which you can finde here.
To install and run the code, run the following in your terminal:
$ pip install -r pip-requirements.txt $ git clone https://github.com/clld/concepticon-data.git $ cd concepticon-data
This gist describes, how you can extract sublists from a wordlist in LingPy with help of the pyconcepticon API. See https://calc.hypotheses.org/date/2018/07 for details on the code and additional explanations.