@inproceedings{chen-etal-2022-lexicon,
title = "Lexicon of Changes: Towards the Evaluation of Diachronic Semantic Shift in {C}hinese",
author = "Chen, Jing and
Chersoni, Emmanuele and
Huang, Chu-ren",
editor = "Tahmasebi, Nina and
Montariol, Syrielle and
Kutuzov, Andrey and
Hengchen, Simon and
Dubossarsky, Haim and
Borin, Lars",
booktitle = "Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.lchange-1.11",
doi = "10.18653/v1/2022.lchange-1.11",
pages = "113--118",
abstract = "Recent research has brought a wind of using computational approaches to the classic topic of semantic change, aiming to tackle one of the most challenging issues in the evolution of human language. While several methods for detecting semantic change have been proposed, such studies are limited to a few languages, where evaluation datasets are available. This paper presents the first dataset for evaluating Chinese semantic change in contexts preceding and following the Reform and Opening-up, covering a 50-year period in Modern Chinese. Following the DURel framework, we collected 6,000 human judgments for the dataset. We also reported the performance of alignment-based word embedding models on this evaluation dataset, achieving high and significant correlation scores.",
}
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%0 Conference Proceedings
%T Lexicon of Changes: Towards the Evaluation of Diachronic Semantic Shift in Chinese
%A Chen, Jing
%A Chersoni, Emmanuele
%A Huang, Chu-ren
%Y Tahmasebi, Nina
%Y Montariol, Syrielle
%Y Kutuzov, Andrey
%Y Hengchen, Simon
%Y Dubossarsky, Haim
%Y Borin, Lars
%S Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F chen-etal-2022-lexicon
%X Recent research has brought a wind of using computational approaches to the classic topic of semantic change, aiming to tackle one of the most challenging issues in the evolution of human language. While several methods for detecting semantic change have been proposed, such studies are limited to a few languages, where evaluation datasets are available. This paper presents the first dataset for evaluating Chinese semantic change in contexts preceding and following the Reform and Opening-up, covering a 50-year period in Modern Chinese. Following the DURel framework, we collected 6,000 human judgments for the dataset. We also reported the performance of alignment-based word embedding models on this evaluation dataset, achieving high and significant correlation scores.
%R 10.18653/v1/2022.lchange-1.11
%U https://aclanthology.org/2022.lchange-1.11
%U https://doi.org/10.18653/v1/2022.lchange-1.11
%P 113-118
Markdown (Informal)
[Lexicon of Changes: Towards the Evaluation of Diachronic Semantic Shift in Chinese](https://aclanthology.org/2022.lchange-1.11) (Chen et al., LChange 2022)
ACL