Korpuslinguistik
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The metadata management system for speech corpora “memasysco” has been developed at the Institut für Deutsche Sprache (IDS) and is applied for the first time to document the speech corpus “German Today”. memasysco is based on a data model for the documentation of speech corpora and contains two generic XML schemas that drive data capture, XML native database storage, dynamic publishing, and information retrieval. The development of memasysco’s information architecture was mainly based on the ISLE MetaData Initiative (IMDI) guidelines for publishing metadata of linguistic resources. However, since we also have to support the corpus management process in research projects at the IDS, we need a finer atomic granularity for some documentation components as well as more restrictive categories to ensure data integrity. The XML metadata of different speech corpus projects are centrally validated and natively stored in an Oracle XML database. The extension of the system to the management of annotations of audio and video signals (e.g. orthographic and phonetic transcriptions) is planned for the near future.
This paper introduces the recently started DRuKoLA-project that aims at providing mechanisms to flexibly draw virtual comparable corpora from the German Reference Corpus DeReKo and the Reference Corpus of Contemporary Romanian Language CoRoLa in order to use these virtual corpora as empirical basis for contrastive linguistic research.
There have been several attempts to annotate communicative functions to utterances of verbal feedback in English previously. Here, we suggest an annotation scheme for verbal and non-verbal feedback utterances in French including the categories base, attitude, previous and visual. The data comprises conversations, maptasks and negotiations from which we extracted ca. 13,000 candidate feedback utterances and gestures. 12 students were recruited for the annotation campaign of ca. 9,500 instances. Each instance was annotated by between 2 and 7 raters. The evaluation of the annotation agreement resulted in an average best-pair kappa of 0.6. While the base category with the values acknowledgement, evaluation, answer, elicit and other achieves good agreement, this is not the case for the other main categories. The data sets, which also include automatic extractions of lexical, positional and acoustic features, are freely available and will further be used for machine learning classification experiments to analyse the form-function relationship of feedback.
KorAP is a corpus search and analysis platform, developed at the Institute for the German Language (IDS). It supports very large corpora with multiple annotation layers, multiple query languages, and complex licensing scenarios. KorAP’s design aims to be scalable, flexible, and sustainable to serve the German Reference Corpus DEREKO for at least the next decade. To meet these requirements, we have adopted a highly modular microservice-based architecture. This paper outlines our approach: An architecture consisting of small components that are easy to extend, replace, and maintain. The components include a search backend, a user and corpus license management system, and a web-based user frontend. We also describe a general corpus query protocol used by all microservices for internal communications. KorAP is open source, licensed under BSD-2, and available on GitHub.
The aim of the paper is twofold. Firstly, an approach is presented how to select the correct antecedent for an anaphoric element according to the kind of text segments in which both of them occur. Basically, information on logical text structure (e.g. chapters, sections, paragraphs) is used in order to select the antecedent life span of a linguistic expression, i.e. some linguistic expressions are more likely to be chosen as an antecedent throughout the whole text than others. In addition, an appropriate search scope for an anaphora expressed by an expression can be defined according to the document structuring elements that include the linguistic expression. Corpus investigations give rise to the supposition that logical text structure influences the search scope of candidates for antecedents. Second, a solution is presented how to integrate the resources used for anaphora resolution. In this approach, multi-layered XML annotation is used in order to make a set of resources accessible for the anaphora resolution system.
This paper proposes a methodology for querying linguistic data represented in different corpus formats. Examples of the need for queries over such heterogeneous resources are the corpus-based analysis of multimodal phenomena like the interaction of gestures and prosodic features, or syntax-related phenomena like information structure which exceed the expressive power of a tree-centered corpus format. Query languages (QLs) currently under development are strongly connected to corpus formats, like the NITE Object Model (NOM, Carletta et al., 2003) or the Meta-Annotation Infrastructure for ATLAS (MAIA, Laprun and Fiscus, 2002). The parallel development of linguistic query languages and corpus formats is due to the fact that general purpose query languages like XQuery (Boag et al., 2003) do not fulfill the changing needs of linguistically motivated queries, e.g. to give access to (non-)hierarchically organized, theory and language dependent annotations of multi modal signals and/or text. This leads to the problem that existing corpus formats and query languages are hard to reuse. They have to be re developed and re-implemented time-consumingly and expensively for unforeseen tasks. This paper describes an approach for overcoming these problems and a sample application.
This paper describes a corpus of Japanese task-oriented dialogues, i.e. its data, annotations, analysis methodology and preliminary results for the modeling of co-referential phenomena. Current corpus based approaches to co-reference concentrate on textual data from English or other European languages. Hence, the emerging language-general models of co-reference miss input from dialogue data of non-European languages. We aim to fill this gap and contribute to a model of co-reference on various language-specific and language-general levels.
Co-reference annotation and resources: a multilingual corpus of typologically diverse languages
(2002)
This article introduces a dialogue corpus containing data from two typologically different languages, Japanese and Kilivila. The corpus is annotated in accordance with language specific annotation schemes for co-referential and similar relations. The article describes the corpus data, the properties of language specific co-reference in the two languages and a methodology for its annotation. Examples from the corpus show how this methodology is used in the workflow of the annotation process.
We describe a general two-stage procedure for re-using a custom corpus for spoken language system development involving a transformation from character-based markup to XML, and DSSSL stylesheet-driven XML markup enhancement with multiple lexical tag trees. The procedure was used to generate a fully tagged corpus; alternatively with greater economy of computing resources, it can be employed as a parametrised ‘tagging on demand’ filter. The implementation will shortly be released as a public resource together with the corpus (German spoken dialogue, about 500k word form tokens) and lexicon (about 75k word form types).