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We report on a new project building a Natural Language Processing resource for Zulu by making use of resources already available. Combining tagging results with the results of morphological analysis semi-automatically, we expect to reduce the amount of manual work when generating a finely-grained gold standard corpus usable for training a tagger. From the tagged corpus, we plan to extract verb-argument pairs with the aim of compiling a verb valency lexicon for Zulu.
Der vorliegende Beitrag setzt sich mit dem computergestützten Transkriptionsverfahren arabisch-deutscher Gesprächsdaten für interaktionsbezogene Untersuchungen auseinander. Zunächst werden wesentliche methodische Herausforderungen der gesprächsanalytischen Arbeit adressiert: Hinsichtlich der derzeitigen Korpustechnologie ermöglicht die Verwendung von arabischen Schriftzeichen in einem mehrsprachigen, bidirektionalen Transkript keine analysegerechte Rekonstruktion von Reziprozität, Linearität und Simultaneität sprachlichen Handelns. Zudem ist die Verschriftung von arabischen Gesprächsdaten aufgrund der unzureichenden (gesprächsanalytischen) Beschäftigung mit den standardfernen Varietäten und gesprochensprachlichen Phänomenen erschwert. Daher widmet sich der zweite Teil des Beitrags den bisher erarbeiteten und erprobten Lösungsansätzen ̶ einem stringenten, gesprächsanalytisch fundierten Transkriptionssystem für gesprochenes Arabisch.
The paper deals with the process of computer-aided transcription regarding Arabic-German data material for interaction-based studies. First of all, it sheds light upon some major methodological challenges posed by the conversation-analytic approaches: due to current corpus technology, the reciprocity, linearity, and simultaneity of linguistic activities cannot be reconstructed in an analytically proper way when using the Arabic characters in multilingual and bidirectional transcripts. The difficulty of transcribing Arabic encounters is also compounded by the fact that Spoken Arabic as well as its varieties and phenomena have not been standardised enough (for conversation-analytic purposes). Therefore, the second part of this paper is dedicated to preliminary, self-developed solutions, namely a systematic method for transcribing Spoken Arabic.
Content
1 Predicting learner knowledge of individual words using machine learning
Drilon Avdiu, Vanessa Bui, Klára Ptacinová Klimci´ková
2 Automatic Generation and Semantic Grading of Esperanto Sentences in a Teaching Context
Eckhard Bick
3 Toward automatic improvement of language produced by non-native language learners
Mathias Creutz, Eetu Sjöblom
4 Linguistic features and proficiency classification in L2 Spanish and L2 Portuguese
Iria del Ri´o
5 Integrating large-scale web data and curated corpus data in a search engine supporting German literacy education
Sabrina Dittrich, Zarah Weiss, Hannes Schröter, Detmar Meurers
6 Formalism for a language agnostic language learning game and productive grid generation
Sylvain Hatier, Arnaud Bey, Mathieu Loiseau
7 Understanding Vocabulary Growth Through An Adaptive Language Learning System
Elma Kerz, Andreas Burgdorf, Daniel Wiechmann, Stefan Meeger,Yu Qiao, Christian Kohlschein, Tobias Meisen
8 Summarization Evaluation meets Short-Answer Grading
Margot Mieskes, Ulrike Padó
9 Experiments on Non-native Speech Assessment and its Consistency
Ziwei Zhou, Sowmya Vajjala, Seyed Vahid Mirnezami
10 The Impact of Spelling Correction and Task Context on Short Answer Assessment for Intelligent Tutoring Systems
Ramon Ziai, Florian Nuxoll, Kordula De Kuthy, Björn Rudzewitz, Detmar Meurers
In this paper, we describe a data processing pipeline used for annotated spoken corpora of Uralic languages created in the INEL (Indigenous Northern Eurasian Languages) project. With this processing pipeline we convert the data into a loss-less standard format (ISO/TEI) for long-term preservation while simultaneously enabling a powerful search in this version of the data. For each corpus, the input we are working with is a set of files in EXMARaLDA XML format, which contain transcriptions, multimedia alignment, morpheme segmentation and other kinds of annotation. The first step of processing is the conversion of the data into a certain subset of TEI following the ISO standard ’Transcription of spoken language’ with the help of an XSL transformation. The primary purpose of this step is to obtain a representation of our data in a standard format, which will ensure its long-term accessibility. The second step is the conversion of the ISO/TEI files to a JSON format used by the “Tsakorpus” search platform. This step allows us to make the corpora available through a web-based search interface. As an addition, the existence of such a converter allows other spoken corpora with ISO/TEI annotation to be made accessible online in the future.
Die Vermittlung von Fachsprache gewinnt in der heutigen europäischen Gesellschaft, die von 'Bewegungen' unterschiedlicher Art charakterisiert ist, immer mehr an Relevanz, aber die Lernergruppen werden immer differenzierter und die Lehrenden, die meist keine Experten auf dem Fachgebiet sind, haben Schwierigkeiten lernergerechte Kurse zu gestalten, da die Möglichkeiten zur Aus- oder Fortbildung selten sind. Fragen, die offen stehen oder nur teilweise beantwortet wurden, gibt es noch viele und eine einheitliche Antwort ist nicht immer möglich, aber wir möchten trotzdem versuchen, anstatt von Problemfällen auch Experimente und Lösungen vorzustellen. Wir möchten zeigen, wie und mit welchen Mitteln und Werkzeugen Fachsprachen beschrieben werden können und welche Auswirkungen dies im Unterricht haben kann. Nach einem Überblick über die unterschiedlichen Definitionsmöglichkeiten von 'Fachsprache', zeigen wir, welche Auswirkungen die unterschiedlichen Schwerpunkte in der Lehre haben können. Abschließend werden wir ein kleines korpuslinguistisches Experiment vorstellen (Korpus mit den Aufsätzen zum Themenschwerpunkt 'Fachsprache' ZIF 2019-1), um mögliche Anregungen zur Benutzung von Korpora zu geben, da sich Korpora in allen Phasen des Unterrichts (vor, während und danach) sowohl für Lehrende als auch für Lernende positiv auswirken können.
The DRuKoLA project
(2019)
DRuKoLA, the accompanying project in the making of the Corpus of Romanian Language, is a cooperation between German and Romanian computer scientists, corpus linguists and linguists, aiming at linking reference corpora of European languages under one corpus analysis tool able to manage big data. KorAP, the analysis tool developed at the Leibniz Institute for the German Language (Mannheim), is being tailored for the Romanian language in a first attempt to reunite reference corpora under the EuReCo initiative, detailed in this paper. The paper describes the necessary steps of harmonization within KorAP and the corpus of Romanian language and discusses, as one important goal of this project, criteria and ways to build virtual comparable corpora to be used for contrastive linguistic analyses.
The present paper examines a variety of ways in which the Corpus of Contemporary Romanian Language (CoRoLa) can be used. A multitude of examples intends to highlight a wide range of interrogation possibilities that CoRoLa opens for different types of users. The querying of CoRoLa displayed here is supported by the KorAP frontend, through the querying language Poliqarp. Interrogations address annotation layers, such as the lexical, morphological and, in the near future, the syntactical layer, as well as the metadata. Other issues discussed are how to build a virtual corpus, how to deal with errors, how to find expressions and how to identify expressions.
The user interfaces for corpus analysis platforms must provide a high degree of accessibility for ordinary users and at the same time provide the possibility to answer complex research questions. In this paper, we present the design concepts behind the user interface of KorAP, a corpus analysis platform that has evolved into the main gateway to CoRoLa, the Reference Corpus of Contemporary Romanian Language. Based on established principles of user interface design, we show how KorAP addresses the challenge of providing a user-friendly interface for heterogeneous corpus data to a wide range of users with different research questions.