Using Mixed Incentives to Document Xi’an Guanzhong

Juhong Zhan, Yue Jiang, Christopher Cieri*, Mark Liberman, Jiahong Yuan, Yiya Chen, Odette Scharenborg

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

This paper describes our use of mixed incentives and the citizen science portal LanguageARC to prepare, collect and quality control a large corpus of object namings for the purpose of providing speech data to document the under-represented Guanzhong dialect of Chinese spoken in the Shaanxi province in the environs of Xi’an.

Original languageEnglish
Title of host publication2nd Workshop on Novel Incentives in Data Collection from People
Subtitle of host publicationModels, Implementations, Challenges and Results, NIDCP 2022 - Proceedings at LREC 2022 Workshop - Language Resources and Evaluation Conference
EditorsJames Fiumara, Christopher Cieri, Mark Liberman, Chris Callison-Burch
PublisherEuropean Language Resources Association (ELRA)
Pages32-37
Number of pages6
ISBN (Electronic)9782493814050
Publication statusPublished - 2022
Event2nd Workshop on Novel Incentives in Data Collection from People: Models, Implementations, Challenges and Results, NIDCP 2022 - Marseille, France
Duration: 20 Jun 202225 Jun 2022

Publication series

Name2nd Workshop on Novel Incentives in Data Collection from People: Models, Implementations, Challenges and Results, NIDCP 2022 - Proceedings at LREC 2022 Workshop - Language Resources and Evaluation Conference

Conference

Conference2nd Workshop on Novel Incentives in Data Collection from People: Models, Implementations, Challenges and Results, NIDCP 2022
Country/TerritoryFrance
CityMarseille
Period20/06/2225/06/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • annotation
  • language resources
  • linguistic data
  • novel incentives
  • under-resourced languages

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