荷兰2019冠状病毒病新闻发布会上的演讲。

IF 1.7 3区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Daan Schueler, Maarten Marx
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引用次数: 3

摘要

创建了所有荷兰COVID-19新闻发布会的开源语料库,其中的句子根据John Searle的Speech Act分类法进行了注释。它包含了2020年3月6日至2021年4月20日期间举行的所有58场新闻发布会,并有9.441个手动注释的句子。言语行为以一致的方式进行注释,Krippendorff的alpha值为。71。该语料库易于使用,元数据丰富,包含词汇、句法、话语(说话人、问题或答案)特征和有关规则类型的信息。我们从言语行为使用的角度对新闻发布会进行分析,深入了解新闻发布会的言语行为使用随时间的变化,言语行为使用与现实世界现象的关系,新闻发布会的总体结构以及发言人之间的角色划分。言语行为的使用与新闻发布会的类型(即宽松、紧张或中性)以及住院人数之间存在关系。演讲行为课程显示了新闻发布会的首选地点,表明了总体结构。确定了发言者之间的不同角色。我们还研究了使用我们的标记句子集来训练语音行为分类器,并使用最先进的变压器RoBERTa模型实现了0.73的合理精度和0.74的平均倒数秩。补充信息:本文的在线版本包含补充材料:10.1007/s10579-022-09602-7。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Speech acts in the Dutch COVID-19 Press Conferences.

Speech acts in the Dutch COVID-19 Press Conferences.

Speech acts in the Dutch COVID-19 Press Conferences.

Speech acts in the Dutch COVID-19 Press Conferences.

An open source corpus of all Dutch COVID-19 Press Conferences with sentences annotated on the basis of John Searle's Speech Act taxonomy was created. It contains all 58 press conferences held between March 6 2020 and April 20 2021 and has 9.441 manually annotated sentences. Speech acts were annotated in a consistent manner, with a Krippendorff's alpha of .71. The corpus is easy to use and rich in metadata, with lexical, syntactic, discourse (speaker, question or answer) features and information on the type of regulations being present. We analyse the press conferences in terms of speech act usage, giving insight into the use of speech acts over time, the relation of speech act usage to real world phenomena, the general structure of the press conferences and the division of roles between speakers. Relations were found between speech act usage and the type of press conference (i.e. easing, tightening or neutral) as well as the number of hospital admissions. Speech act classes showed preferred locations within the press conferences, indicating a general structure. Distinct roles between speakers were identified. We also investigate the use of our set of labelled sentences for training a speech act classifier and achieve a reasonable accuracy of .73 and a mean reciprocal rank of .74 with the state of the art transformer RoBERTa model.

Supplementary information: The online version of this article contains supplementary material available 10.1007/s10579-022-09602-7.

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来源期刊
Language Resources and Evaluation
Language Resources and Evaluation 工程技术-计算机:跨学科应用
CiteScore
6.50
自引率
3.70%
发文量
55
审稿时长
>12 weeks
期刊介绍: Language Resources and Evaluation is the first publication devoted to the acquisition, creation, annotation, and use of language resources, together with methods for evaluation of resources, technologies, and applications. Language resources include language data and descriptions in machine readable form used to assist and augment language processing applications, such as written or spoken corpora and lexica, multimodal resources, grammars, terminology or domain specific databases and dictionaries, ontologies, multimedia databases, etc., as well as basic software tools for their acquisition, preparation, annotation, management, customization, and use. Evaluation of language resources concerns assessing the state-of-the-art for a given technology, comparing different approaches to a given problem, assessing the availability of resources and technologies for a given application, benchmarking, and assessing system usability and user satisfaction.
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