pwc-archive/papers-with-abstracts huggingface dataset:
Quick and Simple Approach for Detecting Hate Speech in Arabic Tweets
Authors: Abeer Abuzayed, Tamer Elsayed
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: 8k

As the use of social media platforms increases extensively to freely communicate and share opinions, hate speech becomes an outstanding problem that requires urgent attention. This paper focuses on the problem of detecting hate speech in Arabic tweets. To tackle the problem efficiently, we adopt a {``}quick and simple{''} approach by which we investigate the effectiveness of 15 classical (e.g., SVM) and neural (e.g., CNN) learning models, while exploring two different term representations. Our experiments on 8k labelled dataset show that the best neural learning models outperform the classical ones, while distributed term representation is more effective than statistical bag-of-words representation. Overall, our best classifier (that combines both CNN and RNN in a joint architecture) achieved 0.73 macro-F1 score on the dev set, which significantly outperforms the majority-class baseline that achieves 0.49, proving the effectiveness of our {``}quick and simple{''} approach.
New Developments in the Polish Parliamentary Corpus
Authors: Maciej Ogrodniczuk, Bart{\l}omiej Nito{\'n}
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

This short paper presents the current (as of February 2020) state of preparation of the Polish Parliamentary Corpus (PPC){---}an extensive collection of transcripts of Polish parliamentary proceedings dating from 1919 to present. The most evident developments as compared to the 2018 version is harmonization of metadata, standardization of document identifiers, uploading contents of all documents and metadata to the database (to enable easier modification, maintenance and future development of the corpus), linking utterances to the political ontology, linking corpus texts to source data and processing historical documents.
Anf\"oranden: Annotated and Augmented Parliamentary Debates from Sweden
Authors: Stian R{\o}dven Eide
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

The Swedish parliamentary debates have been available since 2010 through the parliament{'}s open data web site Riksdagens {\"o}ppna data. While fairly comprehensive, the structure of the data can be hard to understand and its content is somewhat noisy for use as a quality language resource. In order to make them easier to use and process {--} in particular for language technology research, but also for political science and other fields with an interest in parliamentary data {--} we have published a large selection of the debates in a cleaned and structured format, annotated with linguistic information and augmented with semantic links. Especially prevalent in the parliament{'}s data were end-line hyphenations {--} something that tokenisers generally are not equipped for {--} and a lot of the effort went into resolving these. In this paper, we provide detailed descriptions of the structure and contents of the resource, and explain how it differs from the parliament{'}s own version.
IGC-Parl: Icelandic Corpus of Parliamentary Proceedings
Authors: Stein{\th}{\'o}r Steingr{\'\i}msson, Starka{\dh}ur Barkarson, Gunnar Thor {\"O}rn{\'o}lfsson
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

We describe the acquisition, annotation and encoding of the corpus of the Althingi parliamentary proceedings. The first version of the corpus includes speeches from 1911-2019. It comprises 406 thousand speeches and over 219 million words. The corpus has been automatically part-of-speech tagged and lemmatised. It is annotated with extensive metadata about the speeches, speakers and political parties, including speech topic, whether the speaker is in the government coalition or opposition, age and gender of speaker at the time of delivery, references to sound and video recordings and more. The corpus is encoded in accordance with the Text Encoding Initiative (TEI) Guidelines and conforms to the Parla-CLARIN schema. We plan to update the corpus annually and its major versions will be archived in the CLARIN.IS repository. It is available for download and search using the KORP concordance tool. Furthermore, information on word frequency are accessible in a custom made web application and an n-gram viewer.
Compiling Czech Parliamentary Stenographic Protocols into a Corpus
Authors: Barbora Hladka, Maty{\'a}{\v{s}} Kopp, Pavel Stra{\v{n}}{\'a}k
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

The Parliament of the Czech Republic consists of two chambers: the Chamber of Deputies (Lower House) and the Senate (Upper House). In our work, we focus on agenda and documents that relate to the Chamber of Deputies exclusively. We pay particular attention to stenographic protocols that record the Chamber of Deputies{'} meetings. Our overall goal is to (1) compile the protocols into a ParlaCLARIN TEI encoded corpus, (2) make this corpus accessible and searchable in the TEITOK web-based platform, (3) annotate the corpus using the modules available in TEITOK, e.g. detect and recognize named entities, and (4) highlight the annotations in TEITOK. In addition, we add two more goals that we consider innovative: (5) update the corpus every time a new stenographic protocol is published online by the Chambers of Deputies and (6) expose the annotations as the linked open data in order to improve the protocols{'} interoperability with other existing linked open data. This paper is devoted to the goals (1) and (5).
Unfinished Business: Construction and Maintenance of a Semantically Tagged Historical Parliamentary Corpus, UK Hansard from 1803 to the present day
Authors: Matthew Coole, Paul Rayson, John Mariani
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Part-Of-Speech Tagging

Creating, curating and maintaining modern political corpora is becoming an ever more involved task. As interest from various social bodies and the general public in political discourse grows so too does the need to enrich such datasets with metadata and linguistic annotations. Beyond this, such corpora must be easy to browse and search for linguists, social scientists, digital humanists and the general public. We present our efforts to compile a linguistically annotated and semantically tagged version of the Hansard corpus from 1803 right up to the present day. This involves combining multiple sources of documents and transcripts. We describe our toolchain for tagging; using several existing tools that provide tokenisation, part-of-speech tagging and semantic annotations. We also provide an overview of our bespoke web-based search interface built on LexiDB. In conclusion, we examine the completed corpus by looking at four case studies including semantic categories made available by our toolchain.
The siParl corpus of Slovene parliamentary proceedings
Authors: Andrej Pancur, Toma{\v{z}} Erjavec
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Translation

The paper describes the process of acquisition, up-translation, encoding, annotation, and distribution of siParl, a collection of the parliamentary debates from the Assembly of the Republic of Slovenia from 1990{--}2018, covering the period from just before Slovenia became an independent country in 1991, and almost up to the present. The entire corpus, comprising over 8 thousand sessions, 1 million speeches and 200 million words was uniformly encoded in accordance with the TEI-based Parla-CLARIN schema for encoding corpora of parliamentary debates, and contains extensive meta-data about the speakers, a typology of sessions etc. and structural and editorial annotations. The corpus was also part-of-speech tagged and lemmatised using state-of-the-art tools. The corpus is maintained on GitHub with its major versions archived in the CLARIN.SI repository and is available for linguistic analysis in the scope of the on-line CLARIN.SI concordancers, thus offering an invaluable resource for scholars studying Slovenian political history.
Who mentions whom? Recognizing political actors in proceedings
Authors: Lennart Kerkvliet, Jaap Kamps, Maarten Marx
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

We show that it is straightforward to train a state of the art named entity tagger (spaCy) to recognize political actors in Dutch parliamentary proceedings with high accuracy. The tagger was trained on 3.4K manually labeled examples, which were created in a modest 2.5 days work. This resource is made available on github. Besides proper nouns of persons and political parties, the tagger can recognize quite complex definite descriptions referring to cabinet ministers, ministries, and parliamentary committees. We also provide a demo search engine which employs the tagged entities in its SERP and result summaries.
Challenges of Applying Automatic Speech Recognition for Transcribing EU Parliament Committee Meetings: A Pilot Study
Authors: Hugo de Vos, Suzan Verberne
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), speech-recognition, Speech Recognition

Challenges of Applying Automatic Speech Recognition for Transcribing EUParliament Committee Meetings: A Pilot StudyHugo de Vos and Suzan VerberneInstitute of Public Administration and Leiden Institute of Advanced Computer Science, Leiden Universityh.p.de.vos@fgga.leidenuniv.nl, s.verberne@liacs.leidenuniv.nlAbstractWe tested the feasibility of automatically transcribing committee meetings of the European Union parliament with the use of AutomaticSpeech Recognition techniques. These committee meetings contain more valuable information for political science scholars than theplenary meetings since these meetings showcase actual debates opposed to the more formal plenary meetings. However, since there areno transcriptions of those meetings, they are a lot less accessible for research than the plenary meetings, of which multiple corpora exist.We explored a freely available ASR application and analysed the output in order to identify the weaknesses of an out-of-the box system.We followed up on those weaknesses by proposing directions for optimizing the ASR for our goals. We found that, despite showcasingacceptable results in terms of Word Error Rate, the model did not yet suffice for the purpose of generating a data set for use in PoliticalScience. The application was unable to successfully recognize domain specific terms and names. To overcome this issue, future researchwill be directed at using domain specific language models in combination with off-the-shelf acoustic models.
Parsing Icelandic Al\thingi Transcripts: Parliamentary Speeches as a Genre
Authors: Kristj{\'a}n R{\'u}narsson, Einar Freyr Sigur{\dh}sson
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

We introduce a corpus of transcripts from Al{\th}ingi, the Icelandic parliament. The corpus is syntactically parsed for phrase structure according to the annotation scheme of the Icelandic Parsed Historical Corpus (IcePaHC). This addition to IcePaHC makes it more diverse with respect to text types and we argue that having a syntactically parsed corpus facilitates research on differt types of texts. We furthermore argue that the speech corpus can be treated somewhat like spoken language even though the transcripts differ in various ways from daily spoken language. We also compare this text type to other types and argue that this genre can shed light on their properties. Finally, we exhibit how this addition to IcePaHC has helped us in identifying and solving issues with our parsing scheme.
Identifying Parties in Manifestos and Parliament Speeches
Authors: Costanza Navarretta, Dorte Haltrup Hansen
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

This paper addresses differences in the word use of two left-winged and two right-winged Danish parties, and how these differences reflecting some of the basic stances of the parties can be used to automatically identify the party of politicians from their speeches. In the first study, the most frequent and characteristic lemmas in the manifestos of the political parties are analysed. The analysis shows that the most frequently occurring lemmas in the manifestos reflect either the ideology or the position of the parties towards specific subjects, confirming for Danish preceding studies of English and German manifestos. Successively, we scaled our analysis applying machine learning on different language models built on the transcribed speeches by members of the same parties in the Parliament (Hansards) in order to determine to what extent it is possible to predict the party of the politicians from the speeches. The speeches used are a subset of the Danish Parliament corpus 2009{--}2017. The best models resulted in a weighted F1-score of 0.57. These results are significantly better than the results obtained by the majority classifier (F1-score = 0.11) and by chance results (0.25) and show that building language models over the speeches used by politicians can be used to identify the politicians{'} party even if they debate about the same subjects and thus often use the same terminology in many cases. In the future, we will include the subject of the speeches in the prediction experiments
Comparing Lexical Usage in Political Discourse across Diachronic Corpora
Authors: Klaus Hofmann, Anna Marakasova, Andreas Baumann, Julia Neidhardt, Tanja Wissik
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Additive models, Time Series, Time Series Analysis

Most diachronic studies on both lexico-semantic change and political language usage are based on individual or comparable corpora. In this paper, we explore ways of studying the stability (and changeability) of lexical usage in political discourse across two corpora which are substantially different in structure and size. We present a case study focusing on lexical items associated with political parties in two diachronic corpora of Austrian German, namely a diachronic media corpus (AMC) and a corpus of parliamentary records (ParlAT), and measure the cross-temporal stability of lexical usage over a period of 20 years. We conduct three sets of comparative analyses investigating a) the stability of sets of lexical items associated with the three major political parties over time, b) lexical similarity between parties, and c) the similarity between the lexical choices in parliamentary speeches by members of the parties vis-{`}a-vis the media{'}s reporting on the parties. We employ time series modeling using generalized additive models (GAMs) to compare the lexical similarities and differences between parties within and across corpora. The results show that changes observed in these measures can be meaningfully related to political events during that time.
The Europeanization of Parliamentary Debates on Migration in Austria, France, Germany, and the Netherlands
Authors: Andreas Blaette, Simon Gehlhar, Christoph Leonhardt
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

Corpora of plenary debates in national parliaments are available for many European states. For comparative research on political discourse, a persisting problem is that the periods covered by corpora differ and that a lack of standardization of data formats inhibits the integration of corpora into a single analytical framework. The solution we pursue is a {`}Framework for Parsing Plenary Protocols{'} (frappp), which has been used to prepare corpora of the Assembl{\'e}e Nationale ({`}{`}ParisParl{''}), the German Bundestag ({`}{`}GermaParl{''}), the Tweede Kamer of the Netherlands ({`}{`}TweedeTwee{''}), and the Austrian Nationalrat ({`}{`}AustroParl{''}) for the first two decades of the 21st century (2000-2019). To demonstrate the usefulness of the data gained, we investigate the Europeanization of migration debates in these Western European countries of immigration, i.e. references to a European dimension of policy-making in speeches on migration and integration. Based on a segmentation of the corpora into speeches, the method we use is topic modeling, and the analysis of joint occurrences of topics indicating migration and European affairs, respectively. A major finding is that after 2015, we see an increasing Europeanization of migration debates in the small EU member states in our sample (Austria and the Netherlands), and a regression of respective Europeanization in France and {--} more notably {--} in Germany.
Querying a large annotated corpus of parliamentary debates
Authors: Sascha Diwersy, Giancarlo Luxardo
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

The TAPS corpus makes it possible to share a large volume of French parliamentary data. The TEI-compliant approach behind its design choices facilitates the publishing and the interoperability of data, but also the implementation of exploratory data analysis techniques in order to process institutional or political discourse. We demonstrate its application to the debates occurred in the context of a specific legislative process, which generated a strong opposition.
Endangered African Languages Featured in a Digital Collection: The Case of the ǂKhomani San, Hugh Brody Collection
Authors: Kerry Jones, Sanjin Muftic
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

The ǂKhomani San, Hugh Brody Collection features the voices and history of indigenous hunter gatherer descendants in three endangered languages namely, N|uu, Kora and Khoekhoe as well as a regional dialect of Afrikaans. A large component of this collection is audio-visual (legacy media) recordings of interviews conducted with members of the community by Hugh Brody and his colleagues between 1997 and 2012, referring as far back as the 1800s. The Digital Library Services team at the University of Cape Town aim to showcase the collection digitally on the UCT-wide Digital Collections platform, Ibali which runs on Omeka-S. In this paper we highlight the importance of such a collection in the context of South Africa, and the ethical steps that were taken to ensure the respect of the ǂKhomani San as their stories get uploaded onto a repository and become accessible to all. We will also feature some of the completed collection on Ibali and guide the reader through the organisation of the collection on the Omeka-S backend. Finally, we will outline our development process, from digitisation to repository publishing as well as present some of the challenges in data clean-up, the curation of legacy media, multi-lingual support, and site organisation.
Usability and Accessibility of Bantu Language Dictionaries in the Digital Age: Mobile Access in an Open Environment
Authors: Thomas Eckart, Sonja Bosch, Uwe Quasthoff, Erik K{\"o}rner, Dirk Goldhahn, Simon Kaleschke
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: LEMMA, Word Embeddings

This contribution describes a free and open mobile dictionary app based on open dictionary data. A specific focus is on usability and user-adequate presentation of data. This includes, in addition to the alphabetical lemma ordering, other vocabulary selection, grouping, and access criteria. Beyond search functionality for stems or roots {--} required due to the morphological complexity of Bantu languages {--} grouping of lemmas by subject area of varying difficulty allows customization. A dictionary profile defines available presentation options of the dictionary data in the app and can be specified according to the needs of the respective user group. Word embeddings and similar approaches are used to link to semantically similar or related words. The underlying data structure is open for monolingual, bilingual or multilingual dictionaries and also supports the connection to complex external resources like Wordnets. The application in its current state focuses on Xhosa and Zulu dictionary data but more resources will be integrated soon.
Complex Setswana Parts of Speech Tagging
Authors: Gabofetswe Malema, Boago Okgetheng, Bopaki Tebalo, Moffat Motlhanka, Goaletsa Rammidi
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Sentence, TAG

Setswana language is one of the Bantu languages written disjunctively. Some of its parts of speech such as qualificatives and some adverbs are made up of multiple words. That is, the part of speech is made up of a group of words. The disjunctive style of writing poses a challenge when a sentence is tokenized or when tagging. A few studies have been done on identification of multi-word parts of speech. In this study we go further to tokenize complex parts of speech which are formed by extending basic forms of multi-word parts of speech. The parts of speech are extended by recursively concatenating more parts of speech to a basic form of parts of speech. We developed rules for building complex relative parts of speech. A morphological analyzer and Python NLTK are used to tag individual words and basic forms of multi-word parts of speech. Developed rules are then used to identify complex parts of speech. Results from a 300 sentence text files give a performance of 74{\%}. The tagger fails when it encounters expansion rules not implemented and when tagging by the morphological analyzer is incorrect.
Comparing Neural Network Parsers for a Less-resourced and Morphologically-rich Language: Amharic Dependency Parser
Authors: Binyam Ephrem Seyoum, Yusuke Miyao, Baye Yimam Mekonnen
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: POS, POS Tagging

In this paper, we compare four state-of-the-art neural network dependency parsers for the Semitic language Amharic. As Amharic is a morphologically-rich and less-resourced language, the out-of-vocabulary (OOV) problem will be higher when we develop data-driven models. This fact limits researchers to develop neural network parsers because the neural network requires large quantities of data to train a model. We empirically evaluate neural network parsers when a small Amharic treebank is used for training. Based on our experiment, we obtain an 83.79 LAS score using the UDPipe system. Better accuracy is achieved when the neural parsing system uses external resources like word embedding. Using such resources, the LAS score for UDPipe improves to 85.26. Our experiment shows that the neural networks can learn dependency relations better from limited data while segmentation and POS tagging require much data.
Mobilizing Metadata: Open Data Kit (ODK) for Language Resource Development in East Africa
Authors: Richard Griscom
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

Linguistic fieldworkers collect and archive metadata as part of the language resources (LRs) that they create, but they often work in resource-constrained environments that prevent them from using computers for data entry. In such situations, linguists must complete time-consuming and error-prone digitization tasks that limit the quantity and quality of the resources and metadata that they produce (Thieberger {\&} Berez 2012; Margetts {\&} Margetts 2012). This paper describes a method for entering linguistic metadata into mobile devices using the Open Data Kit (ODK) platform, a suite of open source tools designed for mobile data collection.
A Computational Grammar of Ga
Authors: Lars Hellan
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

The paper describes aspects of an HPSG style computational grammar of the West African language Ga (a Kwa language spoken in the Accra area of Ghana). As a Volta Basin Kwa language, Ga features many types of multiverb expressions and other particular constructional patterns in the verbal and nominal domain. The paper highlights theoretical and formal features of the grammar motivated by these phenomena, some of them possibly innovative to the formal framework. As a so-called deep grammar of the language, it hosts a rich lexical structure, and we describe ways in which the grammar builds on previously available lexical resources. We outline an environment of current resources in which the grammar is part, and lines of research and development in which it and its environment can be used.