P2: Mündliche Korpora
Refine
Document Type
- Article (22)
- Part of a Book (22)
- Conference Proceeding (20)
- Part of Periodical (3)
- Book (1)
- Doctoral Thesis (1)
- Preprint (1)
Language
- English (36)
- German (33)
- Multiple languages (1)
Has Fulltext
- yes (70)
Keywords
- Korpus <Linguistik> (43)
- Gesprochene Sprache (26)
- Deutsch (22)
- Konversationsanalyse (13)
- Forschungsdaten (12)
- Annotation (10)
- Datenmanagement (9)
- Interaktion (9)
- Mündliche Kommunikation (7)
- Transkription (7)
Publicationstate
- Veröffentlichungsversion (36)
- Zweitveröffentlichung (32)
- Postprint (9)
Reviewstate
Publisher
- European Language Resources Association (8)
- Linköping University Electronic Press (5)
- Association for Computational Linguistics (4)
- de Gruyter (4)
- CLARIN (3)
- Leibniz-Institut für Deutsche Sprache (IDS) (3)
- Narr (3)
- Narr Francke Attempto (3)
- Universitäts- und Landesbibliothek Darmstadt (3)
- Verlag für Gesprächsforschung (3)
The newest generation of speech technology caused a huge increase of audio-visual data nowadays being enhanced with orthographic transcripts such as in automatic subtitling in online platforms. Research data centers and archives contain a range of new and historical data, which are currently only partially transcribed and therefore only partially accessible for systematic querying. Automatic Speech Recognition (ASR) is one option of making that data accessible. This paper tests the usability of a state-of-the-art ASR-System on a historical (from the 1960s), but regionally balanced corpus of spoken German, and a relatively new corpus (from 2012) recorded in a narrow area. We observed a regional bias of the ASR-System with higher recognition scores for the north of Germany vs. lower scores for the south. A detailed analysis of the narrow region data revealed – despite relatively high ASR-confidence – some specific word errors due to a lack of regional adaptation. These findings need to be considered in decisions on further data processing and the curation of corpora, e.g. correcting transcripts or transcribing from scratch. Such geography-dependent analyses can also have the potential for ASR-development to make targeted data selection for training/adaptation and to increase the sensitivity towards varieties of pluricentric languages.
We present web services which implement a workflow for transcripts of spoken language following the TEI guidelines, in particular ISO 24624:2016 “Language resource management – Transcription of spoken language”. The web services are available at our website and will be available via the CLARIN infrastructure, including the Virtual Language Observatory and WebLicht.
This paper presents the QUEST project and describes concepts and tools that are being developed within its framework. The goal of the project is to establish quality criteria and curation criteria for annotated audiovisual language data. Building on existing resources developed by the participating institutions earlier, QUEST develops tools that could be used to facilitate and verify adherence to these criteria. An important focus of the project is making these tools accessible for researchers without substantial technical background and helping them produce high-quality data. The main tools we intend to provide are the depositors’ questionnaire and automatic quality assurance, both developed as web applications. They are accompanied by a Knowledge base, which will contain recommendations and descriptions of best practices established in the course of the project. Conceptually, we split linguistic data into three resource classes (data deposits, collections and corpora). The class of a resource defines the strictness of the quality assurance it should undergo. This division is introduced so that too strict quality criteria do not prevent researchers from depositing their data.
As a part of the ZuMult-project, we are currently modelling a backend architecture that should provide query access to corpora from the Archive of Spoken German (AGD) at the Leibniz-Institute for the German Language (IDS). We are exploring how to reuse existing search engine frameworks providing full text indices and allowing to query corpora by one of the corpus query languages (QLs) established and actively used in the corpus research community. For this purpose, we tested MTAS - an open source Lucene-based search engine for querying on text with multilevel annotations. We applied MTAS on three oral corpora stored in the TEI-based ISO standard for transcriptions of spoken language (ISO 24624:2016). These corpora differ from the corpus data that MTAS was developed for, because they include interactions with two and more speakers and are enriched, inter alia, with timeline-based annotations. In this contribution, we report our test results and address issues that arise when search frameworks originally developed for querying written corpora are being transferred into the field of spoken language.
How Do Speakers Define the Meaning of Expressions? The Case of German x heißt y (“x means y”)
(2020)
To secure mutual understanding in interaction, speakers sometimes explain or negotiate expressions. Adopting a conversation analytic and interaction linguistic approach, I examine how participants explain which kinds of expressions in different sequential environments, using the format x heißt y (“x means y”). When speakers use it to clarify technical terms or foreign words that are unfamiliar to co-participants, they often provide a situationally anchored definition that however is rather context-free and therefore transferable to future situations. When they explain common (but indexical, ambiguous, polysemous, or problematic) expressions instead, speakers always design their explanation strongly connected to the local context, building on situational circumstances. I argue that x heißt y definitions in interaction do not meet the requirements of scientific or philosophical definitions but that this is irrelevant for the situational exigencies speakers face.
This article describes the development of the digital infrastructure at a research data centre for audio-visual linguistic research data, the Hamburg Centre for Language Corpora (HZSK) at the University of Hamburg in Germany, over the past ten years. The typical resource hosted in the HZSK Repository, the core component of the infrastructure, is a collection of recordings with time-aligned transcripts and additional contextual data, a spoken language corpus. Since the centre has a thematic focus on multilingualism and linguistic diversity and provides its service to researchers within linguistics and other disciplines, the development of the infrastructure was driven by diverse usage scenarios and user needs on the one hand, and by the common technical requirements for certified service centres of the CLARIN infrastructure on the other. Beyond the technical details, the article also aims to be a contribution to the discussion on responsibilities and services within emerging digital research data infrastructures and the fundamental issues in sustainability of research software engineering, concluding that in order to truly cater to user needs across the research data lifecycle, we still need to bridge the gap between discipline-specific research methods in the process of digitalisation and generic digital research data management approaches.
This paper describes the development of a systematic approach to the creation, management and curation of linguistic resources, particularly spoken language corpora. It also presents first steps towards a framework for continuous quality control to be used within external research projects by non-technical users, and discuss various domain and discipline specific problems and individual solutions. The creation of spoken language corpora is not only a time-consuming and costly process, but the created resources often represent intangible cultural heritage, containing recordings of, for example, extinct languages or historical events. Since high quality resources are needed to enable re-use in as many future contexts as possible, researchers need to be provided with the necessary means for quality control. We believe that this includes methods and tools adapted to Humanities researchers as non-technical users, and that these methods and tools need to be developed to support existing tasks and goals of research projects.
Towards Comprehensive Definitions of Data Quality for Audiovisual Annotated Language Resources
(2020)
Though digital infrastructures such as CLARIN have been successfully established and now provide large collections of digital resources, the lack of widely accepted standards for data quality and documentation still makes re-use of research data a difficult endeavour, especially for more complex resource types. The article gives a detailed overview over relevant characteristics of audiovisual annotated language resources and reviews possible approaches to data quality in terms of their suitability for the current context. Conclusively, various strategies are suggested in order to arrive at comprehensive and adequate definitions of data quality for this particular resource type.
In this article, we describe a user support solution for the digital humanities. As a case study, we show the development of the CLARIN-D Helpdesk from 2013 into the current support solution that has been extended for several other CLARIN-related software and projects and the DARIAH-ERIC. Furthermore, we describe a way towards a common support platform for CLARIAH-DE, which is currently in the final phase. We hope to further expand the help desk in the following years in order to act as a hub for user support and a central knowledge resource for the digital humanities not only in the German, but also in the European area and perhaps at some point worldwide.
Jesus in der Alltagssprache
(2020)