Domain bias in distinguishing Flemish and Dutch subtitles

Author:

van Halteren HansORCID

Abstract

AbstractThis paper describes experiments in which I tried to distinguish between Flemish and Netherlandic Dutch subtitles, as originally proposed in the VarDial 2018 Dutch–Flemish Subtitle task. However, rather than using all data as a monolithic block, I divided them into two non-overlapping domains and then investigated how the relation between training and test domains influences the recognition quality. I show that the best estimate of the level of recognizability of the language varieties is derived when training on one domain and testing on another. Apart from the quantitative results, I also present a qualitative analysis, by investigating in detail the most distinguishing features in the various scenarios. Here too, it is with the out-of-domain recognition that some genuine differences between Flemish and Netherlandic Dutch can be found.

Publisher

Cambridge University Press (CUP)

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics,Software

Reference32 articles.

1. Çöltekin Ç., Rama, T. and Blaschke, V. (2018). Tübingen-Oslo team at the VarDial 2018 evaluation campaign: an analysis of n-gram features in language variety identification. In Proceedings of the Fifth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial), Santa Fe, USA, pp. 55–65.

2. Exploring Lexical and Syntactic Features for Language Variety Identification

3. Findings of the VarDial Evaluation Campaign 2017

4. Malmasi, S. , Zampieri, M. , Ljubešić, N. , Nakov, P. , Ali, A. and Tiedemann, J. (2016). Discriminating between similar languages and Arabic dialect identification: a report on the third DSL shared task. In Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial3), pp. 1–14.

5. Overview for the Second Shared Task on Language Identification in Code-Switched Data

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3