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Feature extraction using nPMI

This python script is designed to extract exclusive dialect features of a given dialect area.

Preparation of the data:

You are required to have a categorical dialect data (can be dialect features or multi-aligned segmental data) and a dialect classification based on the same dataset before using this script, see more information about the format below. The classification can be based the cluster analysis of the distances calculated with e.g. Relative Distance Value (Goebl 2018) or based on a user-defined classification (which could also be from the literature).

Format required of input file:

Categorical data in the 'Gabmap' format, i.e. in a location x features tableau. Location is the first column, the rest are the list of aligned segments. The format of the file is recommended to be .csv or .txt, but you can change the settings in the script as well. In terms of the classification of dialects, there can be more than one classification scheme included in this analysis. However, all the classifications must be appended at the end of the dialect data. An illustration of the input file can be found under 'example.csv' (based on the GTRP data from Gabmap.nl).

Before running the script:

Make sure you have added the directory of your input file (line 11) and your output file (line 87). In addition, you also need to specify the number of dialect classification schemes you have in your data in line 20.

How to run the script:

Since this is a .py script, you have to run the script in your terminal (e.g. Anaconda prompt). First, you save this python script on your computer. Then you open your terminal and use 'cd' to change the directory into the same folder as the location where you saved this python script. Next, you type 'python nPMI_feature_extraction.py' and click enter. Next, you will be asked which classification scheme to use for the feature extaction with 'Enter classification:', and you are required to put the exact same name of the column of the classification scheme of interest, and then you click enter. The script should then run automatically, given that there is no error in the previous procedures. When you see 'file exported' on the terminal, it means the output file has been saved to the directory you gave in line 80.

Citation:

Please cite this script along with our article: Sung, H. W. M., & Prokić, J. (2024). Detecting Dialect Features Using Normalised Pointwise Information. Computational Linguistics in the Netherlands Journal, 13, 121–145. Retrieved from (https://www.clinjournal.org/clinj/article/view/177)

Contact:

If you have any questions, please don't hesitate to get in touch with me through h.w.m.sung[at]hum.leidenuniv[dot]nl.

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