@inproceedings{9365dafbaa744dd8a574f3bda8015e4d,
title = "Emotionally-Bridged Cross-Lingual Meta-Learning for Chinese Sexism Detection",
abstract = "Sexism detection remains as an extremely low-resource task for most of the languages including Chinese. To address this issue, we propose a zero-shot cross-lingual method to detect sexist speech in Chinese and perform qualitative and quantitative analyses on the data we employed. The proposed method aims to explicitly model the knowledge transfer process from rich-resource language to low-resource language using metric-based meta-learning. To overcome the semantic disparity between various languages caused by language-specific biases, a common label space of emotions expressed across languages is used to integrate universal emotion features into the meta-learning framework. Experiment results show that the proposed method improves over the state-of-the-art zero-shot cross-lingual classification methods.",
keywords = "Cross-lingual, Meta-learning, Sexist Speech Detection",
author = "Guanlin Li and Praboda Rajapaksha and Reza Farahbakhsh and Noel Crespi",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.; 12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023 ; Conference date: 12-10-2023 Through 15-10-2023",
year = "2023",
month = jan,
day = "1",
doi = "10.1007/978-3-031-44696-2\_49",
language = "English",
isbn = "9783031446955",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "627--639",
editor = "Fei Liu and Nan Duan and Qingting Xu and Yu Hong",
booktitle = "Natural Language Processing and Chinese Computing - 12th National CCF Conference, NLPCC 2023, Proceedings",
}