gendec-with-distilmbert

INPUT: Japanese name in ROMAJI FORM

OUTPUT:

• Label_0: Male
• Label_1: Female

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Gendec: Gender Dection from Japanese Names with Machine Learning

This is the official repository for the Gendec framework from the paper Gendec: Gender Dection from Japanese Names with Machine Learning, which was accepted at the ISDA'23.

Citation Information

@misc{pham2023gendec,
      title={Gendec: A Machine Learning-based Framework for Gender Detection from Japanese Names}, 
      author={Duong Tien Pham and Luan Thanh Nguyen},
      year={2023},
      eprint={2311.11001},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Abstract

Every human has their own name, a fundamental aspect of their identity and cultural heritage. The name often conveys a wealth of information, including details about an individual's background, ethnicity, and, especially, their gender. By detecting gender through the analysis of names, researchers can unlock valuable insights into linguistic patterns and cultural norms, which can be applied to practical applications. Hence, this work presents a novel dataset for Japanese name gender detection comprising 64,139 full names in romaji, hiragana, and kanji forms, along with their biological genders. Moreover, we propose Gendec, a framework for gender detection from Japanese names that leverages diverse approaches, including traditional machine learning techniques or cutting-edge transfer learning models, to predict the gender associated with Japanese names accurately. Through a thorough investigation, the proposed framework is expected to be effective and serve potential applications in various domains.

Dataset

The dataset used in this paper can be found at this repo.

Contact

Please feel free to contact us by email [email protected] if you have any further information!