The SIGTYP 2022 Shared Task on the Prediction of Cognate Reflexes

Johann-Mattis List, Ekaterina Vylomova, Robert Forkel, Nathan Hill, Ryan Cotterell
{"title":"The SIGTYP 2022 Shared Task on the Prediction of Cognate Reflexes","authors":"Johann-Mattis List, Ekaterina Vylomova, Robert Forkel, Nathan Hill, Ryan Cotterell","doi":"10.18653/v1/2022.sigtyp-1.7","DOIUrl":null,"url":null,"abstract":"This study describes the structure and the results of the SIGTYP 2022 shared task on the prediction of cognate reflexes from multilingual wordlists. We asked participants to submit systems that would predict words in individual languages with the help of cognate words from related languages. Training and surprise data were based on standardized multilingual wordlists from several language families. Four teams submitted a total of eight systems, including both neural and non-neural systems, as well as systems adjusted to the task and systems using more general settings. While all systems showed a rather promising performance, reflecting the overwhelming regularity of sound change, the best performance throughout was achieved by a system based on convolutional networks originally designed for image restoration.","PeriodicalId":255232,"journal":{"name":"Proceedings of the 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/2022.sigtyp-1.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

This study describes the structure and the results of the SIGTYP 2022 shared task on the prediction of cognate reflexes from multilingual wordlists. We asked participants to submit systems that would predict words in individual languages with the help of cognate words from related languages. Training and surprise data were based on standardized multilingual wordlists from several language families. Four teams submitted a total of eight systems, including both neural and non-neural systems, as well as systems adjusted to the task and systems using more general settings. While all systems showed a rather promising performance, reflecting the overwhelming regularity of sound change, the best performance throughout was achieved by a system based on convolutional networks originally designed for image restoration.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
关于同源反射预测的SIGTYP 2022共享任务
本研究描述了SIGTYP 2022共享任务对多语言词表同源反射预测的结构和结果。我们要求参与者提交一种系统,该系统可以在相关语言的同源词的帮助下预测单个语言中的单词。训练和惊喜数据基于来自几个语系的标准化多语言词表。四个团队总共提交了八个系统,包括神经系统和非神经系统,以及适应任务的系统和使用更一般设置的系统。虽然所有系统都表现出相当有希望的性能,反映了声音变化的压倒性规律性,但整个系统的最佳性能是基于最初为图像恢复设计的卷积网络的系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Tweaking UD Annotations to Investigate the Placement of Determiners, Quantifiers and Numerals in the Noun Phrase Mockingbird at the SIGTYP 2022 Shared Task: Two Types of Models forthe Prediction of Cognate Reflexes A Transformer Architecture for the Prediction of Cognate Reflexes Bayesian Phylogenetic Cognate Prediction PaVeDa - Pavia Verbs Database: Challenges and Perspectives
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1