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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.
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.
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.
The paper presents a discussion on the main linguistic phenomena of user-generated texts found in web and social media, and proposes a set of annotation guidelines for their treatment within the Universal Dependencies (UD) framework. Given on the one hand the increasing number of treebanks featuring user-generated content, and its somewhat inconsistent treatment in these resources on the other, the aim of this paper is twofold: (1) to provide a short, though comprehensive, overview of such treebanks - based on available literature - along with their main features and a comparative analysis of their annotation criteria, and (2) to propose a set of tentative UD-based annotation guidelines, to promote consistent treatment of the particular phenomena found in these types of texts. The main goal of this paper is to provide a common framework for those teams interested in developing similar resources in UD, thus enabling cross-linguistic consistency, which is a principle that has always been in the spirit of UD.
In the paper we investigate the impact of data size on a Word Sense Disambiguation task (WSD). We question the assumption that the knowledge acquisition bottleneck, which is known as one of the major challenges for WSD, can be solved by simply obtaining more and more training data. Our case study on 1,000 manually annotated instances of the German verb drohen (threaten) shows that the best performance is not obtained when training on the full data set, but by carefully selecting new training instances with regard to their informativeness for the learning process (Active Learning). We present a thorough evaluation of the impact of different sampling methods on the data sets and propose an improved method for uncertainty sampling which dynamically adapts the selection of new instances to the learning progress of the classifier, resulting in more robust results during the initial stages of learning. A qualitative error analysis identifies problems for automatic WSD and discusses the reasons for the great gap in performance between human annotators and our automatic WSD system.
So far, comprehensive grammar descriptions of Northern Sotho have only been available in the form of prescriptive books aiming at teaching the language. This paper describes parts of the first morpho-syntactic description of Northern Sotho from a computational perspective (Faaß, 2010a). Such a description is necessary for implementing rule based, operational grammars. It is also essential for the annotation of training data to be utilised by statistical parsers. The work that we partially present here may hence provide a resource for computational processing of the language in order to proceed with producing linguistic representations beyond tagging, may it be chunking or parsing. The paper begins with describing significant Northern Sotho verbal morpho-syntactics (section 2). It is shown that the topology of the verb can be depicted as a slot system which may form the basis for computational processing (section 3). Note that the implementation of the described rules (section 4) and also coverage tests are ongoing processes upon that we will report in more detail at a later stage.
The Component Metadata Infrastructure (CMDI) in a project on sustainable linguistic resources
(2012)
The sustainable archiving of research data for predefined time spans has become increasingly important to researchers and is stipulated by funding organizations with the obligatory task of being observed by researchers. An important aspect in view of such a sustainable archiving of language resources is the creation of metadata, which can be used for describing, finding and citing resources. In the present paper, these aspects are dealt with from the perspectives of two projects: the German project for Sustainability of Linguistic Data at the University of Tubingen (NaLiDa, cf. http://www.sfs.uni-tuebingen.de/nalida) and the Dutch-Flemish HLT Agency hosted at the Institute for Dutch Lexicology (TST-Centrale, cf.http://www.inl.nl/tst-centrale). Both projects unfold their approaches to the creation of components and profiles using the Component Metadata Infrastructure (CMDI) as underlying metadata schema for resource descriptions, highlighting their experiences as well as advantages and disadvantages in using CMDI.
This paper describes the status of the standardization efforts of a Component Metadata approach for describing Language Resources with metadata. Different linguistic and Language & Technology communities as CLARIN, META-SHARE and NaLiDa use this component approach and see its standardization of as a matter for cooperation that has the possibility to create a large interoperable domain of joint metadata. Starting with an overview of the component metadata approach together with the related semantic interoperability tools and services as the ISOcat data category registry and the relation registry we explain the standardization plan and efforts for component metadata within ISO TC37/SC4. Finally, we present information about uptake and plans of the use of component metadata within the three mentioned linguistic and L&T communities.
Making corpora accessible and usable for linguistic research is a huge challenge in view of (too) big data, legal issues and a rapidly evolving methodology. This does not only affect the design of user-friendly graphical interfaces to corpus analysis tools, but also the availability of programming interfaces supporting access to the functionality of these tools from various analysis and development environments. RKorAPClient is a new research tool in the form of an R package that interacts with the Web API of the corpus analysis platform KorAP, which provides access to large annotated corpora, including the German reference corpus DeReKo with 45 billion tokens. In addition to optionally authenticated KorAP API access, RKorAPClient provides further processing and visualization features to simplify common corpus analysis tasks. This paper introduces the basic functionality of RKorAPClient and exemplifies various analysis tasks based on DeReKo, that are bundled within the R package and can serve as a basic framework for advanced analysis and visualization approaches.
The current state of the art for metadata provision allows for a very flexible approach, catering for the needs of different archives and communities, referring to common data category registries that describe the meaning of a data category at least to authors of metadata. Component models for metadata provisions are for example used by CLARIN and META-SHARE, but there is also an increased flexibility in other metadata schemas such as Dublin Core, which is usually not seen as appropriate for meaningful description of language resources.
Making resources available for others and putting this to a second use in other projects has never been more widely accepted as a sensible efficient way to avoid a waste of efforts and resources. However, when it comes to the details, there is still a vast number of problems. This workshop has aimed at being a forum to address issues and challenges in the concrete work with metadata for LRs, not restricted to a single initiative for archiving LRs. It has allowed for exchange and discussion and we hope that the reader finds the articles here compiled interesting and useful.