Refine
Year of publication
- 2016 (37) (remove)
Document Type
- Conference Proceeding (37) (remove)
Has Fulltext
- yes (37)
Is part of the Bibliography
- no (37) (remove)
Keywords
- Korpus <Linguistik> (14)
- Deutsch (7)
- Computerunterstützte Lexikographie (4)
- Gesprochene Sprache (4)
- Chatten <Kommunikation> (3)
- Component MetaData Infrastructure (CMDI) (3)
- Computerlinguistik (3)
- Französisch (3)
- French (3)
- German (3)
Publicationstate
- Veröffentlichungsversion (37) (remove)
Reviewstate
- (Verlags)-Lektorat (13)
- Peer-Review (10)
Publisher
- European Language Resources Association (ELRA) (7)
- Nisaba (5)
- Association for Computational Linguistics (4)
- Ivane Javakhishvili Tbilisi State University (3)
- CLARIN (2)
- European Language Resources Association (2)
- International Speech Communication Association (2)
- Universität Potsdam (2)
- Academic Publishing Division of the Faculty of Arts of the University of Ljubljana (1)
- Austrian Centre for Digital Humanities, Austrian Academy of Sciences (1)
The paper reports the results of the curation project ChatCorpus2CLARIN. The goal of the project was to develop a workflow and resources for the integration of an existing chat corpus into the CLARIN-D research infrastructure for language resources and tools in the Humanities and the Social Sciences (http://clarin-d.de). The paper presents an overview of the resources and practices developed in the project, describes the added value of the resource after its integration and discusses, as an outlook, to what extent these practices can be considered best practices which may be useful for the annotation and representation of other CMC and social media corpora.
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.
The present paper reports the first results of the compilation and annotation of a blog corpus for German. The main aim of the project is the representation of the blog discourse structure and relations between its elements (blog posts, comments) and participants (bloggers, commentators). The data included in the corpus were manually collected from the scientific blog portal SciLogs. The feature catalogue for the corpus annotation includes three types of information which is directly or indirectly provided in the blog or can be construed by means of statistical analysis or computational tools. At this point, only directly available information (e.g. title of the blog post, name of the blogger etc.) has been annotated. We believe, our blog corpus can be of interest for the general study of blog structure or related research questions as well as for the development of NLP methods and techniques (e.g. for authorship detection).
Annotating Discourse Relations in Spoken Language: A Comparison of the PDTB and CCR Frameworks
(2016)
In discourse relation annotation, there is currently a variety of different frameworks being used, and most of them have been developed and employed mostly on written data. This raises a number of questions regarding interoperability of discourse relation annotation schemes, as well as regarding differences in discourse annotation for written vs. spoken domains. In this paper, we describe ouron annotating two spoken domains from the SPICE Ireland corpus (telephone conversations and broadcast interviews) according todifferent discourse annotation schemes, PDTB 3.0 and CCR. We show that annotations in the two schemes can largely be mappedone another, and discuss differences in operationalisations of discourse relation schemes which present a challenge to automatic mapping. We also observe systematic differences in the prevalence of implicit discourse relations in spoken data compared to written texts,find that there are also differences in the types of causal relations between the domains. Finally, we find that PDTB 3.0 addresses many shortcomings of PDTB 2.0 wrt. the annotation of spoken discourse, and suggest further extensions. The new corpus has roughly theof the CoNLL 2015 Shared Task test set, and we hence hope that it will be a valuable resource for the evaluation of automatic discourse relation labellers.
Converting and Representing Social Media Corpora into TEI: Schema and best practices from CLARIN-D
(2016)
The paper presents results from a curation project within CLARIN-D, in which an existing lMWord corpus of German chat communication has been integrated into the DEREKO and DWDS corpus infrastructures of the CLARIN-D centres at the Institute for the German Language (IDS, Mannheim) and at the Berlin-Brandenburg Academy of Sciences (BBAW, Berlin). The focus is on the solutions developed for converting and representing the corpus in a TEI format.
This paper presents our model of ‘MultiWord Patterns’ (MWPs). MWPs are defined as recurrent frozen schemes with fixed lexical components and productive slots that have a holistic – but not necessarily idiomatic – meaning and/or function, sometimes only on an abstract level. These patterns can only be reconstructed with corpus-driven, iterative (qualitative-quantitative) methods. This methodology includes complex phrase searches, collocation analysis that not only detects significant word pairs, but also significant syntagmatic cotext patterns and slot analysis with our UWV Tool. This tool allows us to bundle KWICs in order to detect the nature of lexical fillers for and to visualize MWP hierarchies.
The Component MetaData Infrastructure (CMDI) is a framework for the creation and usage of metadata formats to describe all kinds of resources in the CLARIN world. To better connect to the library world, and to allow librarians to enter metadata for linguistic resources into their catalogues, a crosswalk from CMDI-based formats to bibliographic standards is required. The general and rather fluid nature of CMDI, however, makes it hard to map arbitrary CMDI schemas to metadata standards such as Dublin Core (DC) or MARC 21, which have a mature, well-defined and fixed set of field descriptors. In this paper, we address the issue and propose crosswalks between CMDI-based profiles originating from the NaLiDa project and DC and MARC 21, respectively.
Languages vary in whether or not their future markers are compatible with non-future modal readings (Tonhauser, 2011b). The present paper proposes that this Variation is determined by the aspectual architecture of a given language, more precisely if and how aspects can be stacked. Building on recent accounts of the temporal interpretation of modals (Matthewson, 2012, 2013; Kratzer, 2012; Chen et al., ta), the paper first sketches an analysis of the temporal readings of the English future marker will and then provides cross-linguistic comparison with a selected, typologically diverse set of languages (Medumba, Hausa, Gitksan, and Greek).
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.
Sentiment analysis has so far focused on the detection of explicit opinions. However, of late implicit opinions have received broader attention, the key idea being that the evaluation of an event type by a speaker depends on how the participants in the event are valued and how the event itself affects the participants. We present an annotation scheme for adding relevant information, couched in terms of so-called effect functors, to German lexical items. Our scheme synthesizes and extends previous proposals. We report on an inter-annotator agreement study. We also present results of a crowdsourcing experiment to test the utility of some known and some new functors for opinion inference where, unlike in previous work, subjects are asked to reason from event evaluation to participant evaluation.
The Component MetaData Infrastructure (CMDI) is the dominant framework for describing language resources according to ISO 24622 (ISO/TC 37/SC 4, 2015). Within the CLARIN world, CMDI has become a huge success. The Virtual Language Observatory (VLO) now holds over 800.000 resources, all described with CMDI-based metadata. With the metadata being harvested from about thirty centres, there is a considerable amount of heterogeneity in the data. In part, there is some use of controlled vocabularies to keep data heterogeneity in check, say when describing the type of a resource, or the country the resource is originating from. However, when CMDI data refers to the names of persons or organisations, strings are used in a rather uncontrolled manner. Here, the CMDI community can learn from libraries and archives who maintain standardised lists for all kinds of names. In this paper, we advocate the use of freely available authority files that support the unique identification of persons, organisations, and more. The systematic use of authority records enhances the quality of the metadata, hence improves the faceted browsing experience in the VLO, and also prepares the sharing of CMDI-based metadata with the data in library catalogues.
Evaluation of Phonatory Behavior of German and French Speakers in Native and Non-native Speech
(2016)
Phonatory behavior of German speakers (GS) and French speakers (FS) in native (L1) and non-native (L2) speech was instrumentally examined. Vowel productions of the two groups were analyzed using a parametrization of phonatory behaviour and phonatory quality properties in the acoustic signal. The behavior of GS is characterized by more strained adduction of the vocal folds whereas FS show more incomplete glottal closure. Furthermore, GS change their phonatory behavior in the foreign language (=French) by adapting phonatory strategies of FS, whereas FS do not show this tendency. In addition, German beginners (BEG) and partly German advanced learners (ADV) are already orientated on production characteristics of the L2. French BEG however retain their phonatory behavior in L2 (=German) by showing less vocal fold adduction in comparison to their L1. French ADV show the opposite behavior. Finally, ADV of the two speaker groups generally show more strained behavior in L2 productions than BEG. The results provide evidence that GS and FS apply different laryngeal phonatory settings and that they altered their settings in L2 differently. Perceptual evaluation of voice quality of the speech material and a correlation analysis between acoustic and perceptual results are suggested for future research.
The paper presents best practices and results from projects in four countries dedicated to the creation of corpora of computer-mediated communication and social media interactions (CMC). Even though there are still many open issues related to building and annotating corpora of that type, there already exists a range of accessible solutions which have been tested in projects and which may serve as a starting point for a more precise discussion of how future standards for CMC corpora may (and should) be shaped like.
We present the IUCL system, based on supervised learning, for the shared task on stance detection. Our official submission, the random forest model, reaches a score of 63.60, and is ranked 6th out of 19 teams. We also use gradient boosting decision trees and SVM and merge all classifiers into an ensemble method. Our analysis shows that random forest is good at retrieving minority classes and gradient boosting majority classes. The strengths of different classifiers wrt. precision and recall complement each other in the ensemble.
The Component MetaData Infrastructure (CMDI) provides a lego-brick framework for the creation, use and re-use of self-defined metadata formats. The design of CMDI can be a force forgood, but history shows that it has often been misunderstood or badly executed. Consequently,it has led the community towards the dark ages of metadata clutter rather than the bright side of semantic interoperability. In this abstract, we report on the condition of CMDI but also outlinean agenda to make the CMDI world a better place to use, share and profit from metadata.
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.