INPUT: Japanese name in ROMAJI FORM

OUTPUT:
- Label_0: Male
- Label_1: Female

--- 

# 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](https://arxiv.org/pdf/2311.11001.pdf), which was accepted at the [ISDA'23](https://www.mirlabs.org/isda23/).

# 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](https://huggingface.co/datasets/tarudesu/gendec-dataset).

# Contact
Please feel free to contact us by email luannt@uit.edu.vn if you have any further information!


{"language": ["ja"], "library_name": "transformers", "tags": ["code"], "datasets": ["tarudesu/gendec-dataset"], "metrics": ["f1"], "pipeline_tag": "text-classification"}
transformers pytorch distilbert text-classification code ja dataset:tarudesu/gendec-dataset arxiv:2311.11001 autotrain_compatible endpoints_compatible region:us