Segmentation of oral corpora

自互动对话研究开始以来，人们就提出了各种各样的口语分割原则。然而，我们仍然缺乏一个既在理论上有充分基础又在实践中可操作的分割系统，这不利于这些语料库在语言分析、语言教学、对比研究和语言技术发展中的使用。因此，该项目为自己设定了一个目标，即发展一种分段方法，这种方法足以分析来自不同层次和不同研究人员群体的互动交谈的数据。本文评估并进一步发展了会话分析、互动语言学、语用学和语料库语言学等方面的文献中提出的分割方法，将这些方法应用于三大类法语和德语各种互动类型的音频和视频记录（分别是CLAPI、ESLO和FOLK数据库）的样本。该项目将产生一个系统的分割准则，适用于不同的交互类型和法语以及德语数据。该项目是第一个分段方法，它既以足够大和多样化的经验基础的综合数据处理为基础，又考虑到跨语言方面。研究结果将提高这三个数据库的可用性，有助于在更普遍的层面上进行口头语料库工作的最佳实践，并增强我们对对话交互结构的理解。因此，该项目将解决对话分析、基于语料库的语言教学、德语和法语口语对比分析以及开发用于交互数据的语言技术方面的当前需求。在方法上，该项目基于两个不同的视角：1)定性的、多维的方法，考虑到分割指标、问题和标准，并导致经过测试和改进的分割准则；2)定量的、一维的方法，基于选定的标准，其中可能的边界由人类注释者根据其与分割的相关性自动识别和分类。这两种方法最初都使用一个试点测试语料库，每个语料库包含10个摘录，每个摘录约10分钟，代表了情况类型方面的总体数据多样性。在项目过程中，语料库将扩展到每种语言的5小时，并考虑到初始阶段的发现。从项目开始，对比方面将被特别考虑。

A great variety of segmentation principles for oral language have been proposed since the beginning of research on talk-in-interaction. However, we still lack a segmentation system that is both theoretically well-founded and practically operationalizable for large and diverse corpora of spoken interaction, and this impairs the use of such corpora for linguistic analysis, for language teaching, for contrastive studies and for the development of language technology. The project has therefore set itself the aim to develop a method of segmentation that is adequate for the analysis of data from talk-in-interaction at different levels and for various communities of researchers. It evaluates and further develops approaches to segmentation put forward in the literature on conversation analysis, interactional linguistics, pragmatics and corpus linguistics by applying them to samples from three large collections of French and German audio and video recordings of various interaction types (the databases CLAPI, ESLO and FOLK, respectively). The project will result in a systematic segmentation guideline applicable across different interaction types and to French as well as German data.The project is the first approach to segmentation that is both based on comprehensive data treatment of a sufficiently large and diverse empirical basis and takes into account the cross-linguistic dimension. The results will improve the usability of the three databases, contribute to best practices for the work with oral corpora on a more general level, and enhance our understanding of structures of talk-in-interaction. The project will thus address current needs in conversation analysis, corpus-based language teaching, contrastive analysis of spoken German and French and in the development of language technology for interaction data.Methodologically, the project is based on two different perspectives: 1) a qualitative, multidimensional approach which takes into account segmentation indices, problems and criteria and leads to tested and improved segmentation guidelines and 2) a quantitative, unidimensional approach based on selected criteria where possible boundaries are automatically identified and classified by human annotators according to their relevance for segmentation. Both approaches initially use a pilot test corpus of 10 excerpts of around 10 minutes each for each language which represents the overall data diversity in terms of situation types. Over the course of the project, the corpus will be extended to 5 hours for each language and takes into account findings from the initial phase. From the beginning of the project, contrastive aspects will be considered particularly.