ethnicseer - a name-ethnicity classifier

ethnicseer ('ethnic-seer') is a name-ethnicity classifier, written in python. It can determine the ethnicity of a given name, using linguistic features such as sequences of characters found in the name and its phonetic pronounciation. ethnicseer comes with a pre-trained model, which can handle the following 12 ethnicities: Middle-Eastern, Chinese, English, French, Vietnam, Spanish, Italian, German, Japanese, Russian, Indian, and Korean. The included pre-trained model can achieve around 84% accuracy on the test data set.

ethnicseer is based on the name-ethnicity classifier, orginally proposed here:

Treeratpituk, Pucktada, and C. Lee Giles. "Name-ethnicity classification and ethnicity-sensitive name matching." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 26. No. 1. 2012.

Paper URL : https://ojs.aaai.org/index.php/AAAI/article/download/8324/8183

Requirements

• abydos
• scikit-learn
• nltk
• python >= 3.7.6

Installation

ethnicseer can be installed using pip

pip install ethnicseer

Usages

Once installed, you can use ethnicseer within your python code to classify whether a Thai name is a person name or a corporate name.

>>> from ethnicseer import EthnicClassifier

>>> ec = EthnicClassifier.load_pretrained_model()
>>> ec.classify_names(['Yūta Nakayama','Marcel Halstenberg','Raphaël Varane'])
['jap', 'ger', 'frn']

Citation

Treeratpituk, Pucktada, and C. Lee Giles. "Name-ethnicity classification and ethnicity-sensitive name matching." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 26. No. 1. 2012.

Author

Pucktada Treeratpituk, Bank of Thailand (pucktadt@bot.or.th)

License

This project is licensed under the Apache Software License 2.0 - see the LICENSE file for details