HW-TSC 2024 Submission for the SemEval-2024 Task 1: Semantic Textual Relatedness (STR)

被引:0
|
作者
Piao, Mengyao [1 ]
Su, Chang [1 ]
Li, Yuang [1 ]
Qiao, Xiaosong [1 ]
Zhao, Xiaofeng [1 ]
Li, Yinglu [1 ]
Zhang, Min [1 ]
Yang, Hao [1 ]
Tu, Dandan [1 ]
机构
[1] Huawei Translat Serv Ctr, Beijing, Peoples R China
关键词
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暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The degree of semantic relatedness of two units of language has long been considered fundamental to understanding meaning. In this paper, we present the system of Huawei Translation Services Center (HW-TSC) for Task 1 of SemEval 2024, which aims to automatically measure the semantic relatedness of sentence pairs in African and Asian languages. The task dataset for this task covers about 14 different languages, These languages originate from five distinct language families and are predominantly spoken in Africa and Asia. For this shared task, we describe our proposed solutions, including ideas and the implementation steps of the task, as well as the outcomes of each experiment on the development dataset. To enhance the performance, we leverage these experimental outcomes and construct an ensemble one. Our results demonstrate that our system achieves impressive performance on test datasets in unsupervised track B and ranked first place for the Punjabi language pair (1).
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页码:1634 / 1638
页数:5
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