Effective Corpus Virtualization
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Student Research Workshop Associated with RANLP 2011, Pages 1–8, Hissar, Bulgaria, 13 September 2011
RANLPStud 2011 Proceedings of the Student Research Workshop associated with The 8th International Conference on Recent Advances in Natural Language Processing (RANLP 2011) 13 September, 2011 Hissar, Bulgaria STUDENT RESEARCH WORKSHOP ASSOCIATED WITH THE INTERNATIONAL CONFERENCE RECENT ADVANCES IN NATURAL LANGUAGE PROCESSING’2011 PROCEEDINGS Hissar, Bulgaria 13 September 2011 ISBN 978-954-452-016-8 Designed and Printed by INCOMA Ltd. Shoumen, BULGARIA ii Preface The Recent Advances in Natural Language Processing (RANLP) conference, already in its eight year and ranked among the most influential NLP conferences, has always been a meeting venue for scientists coming from all over the world. Since 2009, we decided to give arena to the younger and less experienced members of the NLP community to share their results with an international audience. For this reason, further to the first successful and highly competitive Student Research Workshop associated with the conference RANLP 2009, we are pleased to announce the second edition of the workshop which is held during the main RANLP 2011 conference days on 13 September 2011. The aim of the workshop is to provide an excellent opportunity for students at all levels (Bachelor, Master, and Ph.D.) to present their work in progress or completed projects to an international research audience and receive feedback from senior researchers. We have received 31 high quality submissions, among which 6 papers have been accepted as regular oral papers, and 18 as posters. Each submission has been reviewed by -
From CHILDES to Talkbank
From CHILDES to TalkBank Brian MacWhinney Carnegie Mellon University MacWhinney, B. (2001). New developments in CHILDES. In A. Do, L. Domínguez & A. Johansen (Eds.), BUCLD 25: Proceedings of the 25th annual Boston University Conference on Language Development (pp. 458-468). Somerville, MA: Cascadilla. a similar article appeared as: MacWhinney, B. (2001). From CHILDES to TalkBank. In M. Almgren, A. Barreña, M. Ezeizaberrena, I. Idiazabal & B. MacWhinney (Eds.), Research on Child Language Acquisition (pp. 17-34). Somerville, MA: Cascadilla. Recent years have seen a phenomenal growth in computer power and connectivity. The computer on the desktop of the average academic researcher now has the power of room-size supercomputers of the 1980s. Using the Internet, we can connect in seconds to the other side of the world and transfer huge amounts of text, programs, audio and video. Our computers are equipped with programs that allow us to view, link, and modify this material without even having to think about programming. Nearly all of the major journals are now available in electronic form and the very nature of journals and publication is undergoing radical change. These new trends have led to dramatic advances in the methodology of science and engineering. However, the social and behavioral sciences have not shared fully in these advances. In large part, this is because the data used in the social sciences are not well- structured patterns of DNA sequences or atomic collisions in super colliders. Much of our data is based on the messy, ill-structured behaviors of humans as they participate in social interactions. Categorizing and coding these behaviors is an enormous task in itself. -
The General Regionally Annotated Corpus of Ukrainian (GRAC, Uacorpus.Org): Architecture and Functionality
The General Regionally Annotated Corpus of Ukrainian (GRAC, uacorpus.org): Architecture and Functionality Maria Shvedova[0000-0002-0759-1689] Kyiv National Linguistic University [email protected] Abstract. The paper presents the General Regionally Annotated Corpus of Ukrainian, which is publicly available (GRAC: uacorpus.org), searchable online and counts more than 400 million tokens, representing most genres of written texts. It also features regional annotation, i. e. about 50 percent of the texts are attributed with regard to the different regions of Ukraine or countries of the di- aspora. If the author is known, the text is linked to their home region(s). The journalistic texts are annotated with regard to the place where the edition is pub- lished. This feature differs the GRAC from a majority of general linguistic cor- pora. Keywords: Ukrainian language, corpus, diachronic evolution, regional varia- tion. 1 Introduction Currently many major national languages have large universal corpora, known as “reference” corpora (cf. das Deutsche Referenzkorpus – DeReKo) or “national” cor- pora (a label dating back ultimately to the British National Corpus). These corpora are large, representative for different genres of written language, have a certain depth of (usually morphological and metatextual) annotation and can be used for many differ- ent linguistic purposes. The Ukrainian language lacks a publicly available linguistic corpus. Still there is a need of a corpus in the present-day linguistics. Independently researchers compile dif- ferent corpora of Ukrainian for separate research purposes with different size and functionality. As the community lacks a universal tool, a researcher may build their own corpus according to their needs. -
Gold Standard Annotations for Preposition and Verb Sense With
Gold Standard Annotations for Preposition and Verb Sense with Semantic Role Labels in Adult-Child Interactions Lori Moon Christos Christodoulopoulos Cynthia Fisher University of Illinois at Amazon Research University of Illinois at Urbana-Champaign [email protected] Urbana-Champaign [email protected] [email protected] Sandra Franco Dan Roth Intelligent Medical Objects University of Pennsylvania Northbrook, IL USA [email protected] [email protected] Abstract This paper describes the augmentation of an existing corpus of child-directed speech. The re- sulting corpus is a gold-standard labeled corpus for supervised learning of semantic role labels in adult-child dialogues. Semantic role labeling (SRL) models assign semantic roles to sentence constituents, thus indicating who has done what to whom (and in what way). The current corpus is derived from the Adam files in the Brown corpus (Brown, 1973) of the CHILDES corpora, and augments the partial annotation described in Connor et al. (2010). It provides labels for both semantic arguments of verbs and semantic arguments of prepositions. The semantic role labels and senses of verbs follow Propbank guidelines (Kingsbury and Palmer, 2002; Gildea and Palmer, 2002; Palmer et al., 2005) and those for prepositions follow Srikumar and Roth (2011). The corpus was annotated by two annotators. Inter-annotator agreement is given sepa- rately for prepositions and verbs, and for adult speech and child speech. Overall, across child and adult samples, including verbs and prepositions, the κ score for sense is 72.6, for the number of semantic-role-bearing arguments, the κ score is 77.4, for identical semantic role labels on a given argument, the κ score is 91.1, for the span of semantic role labels, and the κ for agreement is 93.9. -
A Massively Parallel Corpus: the Bible in 100 Languages
Lang Resources & Evaluation DOI 10.1007/s10579-014-9287-y ORIGINAL PAPER A massively parallel corpus: the Bible in 100 languages Christos Christodouloupoulos • Mark Steedman Ó The Author(s) 2014. This article is published with open access at Springerlink.com Abstract We describe the creation of a massively parallel corpus based on 100 translations of the Bible. We discuss some of the difficulties in acquiring and processing the raw material as well as the potential of the Bible as a corpus for natural language processing. Finally we present a statistical analysis of the corpora collected and a detailed comparison between the English translation and other English corpora. Keywords Parallel corpus Á Multilingual corpus Á Comparative corpus linguistics 1 Introduction Parallel corpora are a valuable resource for linguistic research and natural language processing (NLP) applications. One of the main uses of the latter kind is as training material for statistical machine translation (SMT), where large amounts of aligned data are standardly used to learn word alignment models between the lexica of two languages (for example, in the Giza?? system of Och and Ney 2003). Another interesting use of parallel corpora in NLP is projected learning of linguistic structure. In this approach, supervised data from a resource-rich language is used to guide the unsupervised learning algorithm in a target language. Although there are some techniques that do not require parallel texts (e.g. Cohen et al. 2011), the most successful models use sentence-aligned corpora (Yarowsky and Ngai 2001; Das and Petrov 2011). C. Christodouloupoulos (&) Department of Computer Science, UIUC, 201 N. -
Better Web Corpora for Corpus Linguistics and NLP
Masaryk University Faculty of Informatics Better Web Corpora For Corpus Linguistics And NLP Doctoral Thesis Vít Suchomel Brno, Spring 2020 Masaryk University Faculty of Informatics Better Web Corpora For Corpus Linguistics And NLP Doctoral Thesis Vít Suchomel Brno, Spring 2020 Declaration Hereby I declare that this paper is my original authorial work, which I have worked out on my own. All sources, references, and literature used or excerpted during elaboration of this work are properly cited and listed in complete reference to the due source. Vít Suchomel Advisor: Pavel Rychlý i Acknowledgements I would like to thank my advisors, prof. Karel Pala and prof. Pavel Rychlý for their problem insight, help with software design and con- stant encouragement. I am also grateful to my colleagues from Natural Language Process- ing Centre at Masaryk University and Lexical Computing, especially Miloš Jakubíček, Pavel Rychlý and Aleš Horák, for their support of my work and invaluable advice. Furthermore, I would like to thank Adam Kilgarriff, who gave me a wonderful opportunity to work for a leading company in the field of lexicography and corpus driven NLP and Jan Pomikálek who helped me to start. I thank to my wife Kateřina who supported me a lot during writing this thesis. Of those who have always accepted me and loved me in spite of my failures, God is the greatest. ii Abstract The internet is used by computational linguists, lexicographers and social scientists as an immensely large source of text data for various NLP tasks and language studies. Web corpora can be built in sizes which would be virtually impossible to achieve using traditional corpus creation methods. -
Book of Abstracts
Book of Abstracts - Journée d’études AFLiCo JET Corpora and Representativeness jeudi 3 et vendredi 4 mai 2018 Bâtiment Max Weber (W) Keynote speakers Dawn Knight et Thomas Egan Plus d’infos : bit.ly/2FPGxvb 1 Table of contents DAY 1 – May 3rd 2018 Thomas Egan, Some perils and pitfalls of non-representativeness 1 Daniel Henke, De quoi sont représentatifs les corpus de textes traduits au juste ? Une étude de corpus comparable-parallèle 1 Ilmari Ivaska, Silvia Bernardini, Adriano Ferraresi, The comparability paradox in multilingual and multi-varietal corpus research: Coping with the unavoidable 2 Antonina Bondarenko, Verbless Sentences: Advantages and Challenges of a Parallel Corpus-based Approach 3 Adeline Terry, The representativeness of the metaphors of death, disease, and sex in a TV show corpus 5 Julien Perrez, Pauline Heyvaert, Min Reuchamps, On the representativeness of political corpora in linguistic research 6 Joshua M. Griffiths, Supplementing Maximum Entropy Phonology with Corpus Data 8 Emmanuelle Guérin, Olivier Baude, Représenter la variation – Revisiter les catégories et les variétés dans le corpus ESLO 9 Caroline Rossi, Camille Biros, Aurélien Talbot, La variation terminologique en langue de spécialité : pour une analyse à plusieurs niveaux 10 Day 2 – May 4rd 2018 Dawn Knight, Representativeness in CorCenCC: corpus design in minoritised languages 11 Frederick Newmeyer, Conversational corpora: When 'big is beautiful' 12 Graham Ranger, How to get "along": in defence of an enunciative and corpus- based approach 13 Thi Thu Trang -
Unit 3: Available Corpora and Software
Corpus building and investigation for the Humanities: An on-line information pack about corpus investigation techniques for the Humanities Unit 3: Available corpora and software Irina Dahlmann, University of Nottingham 3.1 Commonly-used reference corpora and how to find them This section provides an overview of commonly-used and readily available corpora. It is also intended as a summary only and is far from exhaustive, but should prove useful as a starting point to see what kinds of corpora are available. The Corpora here are divided into the following categories: • Corpora of General English • Monitor corpora • Corpora of Spoken English • Corpora of Academic English • Corpora of Professional English • Corpora of Learner English (First and Second Language Acquisition) • Historical (Diachronic) Corpora of English • Corpora in other languages • Parallel Corpora/Multilingual Corpora Each entry contains the name of the corpus and a hyperlink where further information is available. All the information was accurate at the time of writing but the information is subject to change and further web searches may be required. Corpora of General English The American National Corpus http://www.americannationalcorpus.org/ Size: The first release contains 11.5 million words. The final release will contain 100 million words. Content: Written and Spoken American English. Access/Cost: The second release is available from the Linguistic Data Consortium (http://projects.ldc.upenn.edu/ANC/) for $75. The British National Corpus http://www.natcorp.ox.ac.uk/ Size: 100 million words. Content: Written (90%) and Spoken (10%) British English. Access/Cost: The BNC World Edition is available as both a CD-ROM or via online subscription. -
The Bulgarian National Corpus: Theory and Practice in Corpus Design
The Bulgarian National Corpus: Theory and Practice in Corpus Design Svetla Koeva, Ivelina Stoyanova, Svetlozara Leseva, Tsvetana Dimitrova, Rositsa Dekova, and Ekaterina Tarpomanova Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences, Sofia, Bulgaria abstract The paper discusses several key concepts related to the development of Keywords: corpora and reconsiders them in light of recent developments in NLP. corpus design, On the basis of an overview of present-day corpora, we conclude that Bulgarian National Corpus, the dominant practices of corpus design do not utilise the technologies computational adequately and, as a result, fail to meet the demands of corpus linguis- linguistics tics, computational lexicology and computational linguistics alike. We proceed to lay out a data-driven approach to corpus design, which integrates the best practices of traditional corpus linguistics with the potential of the latest technologies allowing fast collection, automatic metadata description and annotation of large amounts of data. Thus, the gist of the approach we propose is that corpus design should be centred on amassing large amounts of mono- and multilin- gual texts and on providing them with a detailed metadata description and high-quality multi-level annotation. We go on to illustrate this concept with a description of the com- pilation, structuring, documentation, and annotation of the Bulgar- ian National Corpus (BulNC). At present it consists of a Bulgarian part of 979.6 million words, constituting the corpus kernel, and 33 Bulgarian-X language corpora, totalling 972.3 million words, 1.95 bil- lion words (1.95×109) altogether. The BulNC is supplied with a com- prehensive metadata description, which allows us to organise the texts according to different principles. -
Psyneuroling
ABSTRACT BOOK International Online Conference of Psycholinguistic and Neurolinguistic Research: Methods, Materials, and Approaches PSYNEUROLING 17-19 December 2020 17 DECEMBER 2020 Session 1 Language and speech in speakers with neurocognitive diseases (1) Niharika Mahajan, Sonal Chitnis, Hemina Dawar, Sujit Jagtap, Poornima Karandikar & Sankar Prasad Gorthi Effect of education on cognitive and communicative abilities in mild dementia: Preliminary study from India (2) Niharika Mahajan, Abhishek Chaudhari, Sonal Chitnis & Sujit Jagtap Cognitive and communicative reserve in bilingual biliterate lady with Alzheimer’s dementia: A case study (3) Ana Varela Suárez Communicative guidelines for caregivers of people with dementia: A decalogue (4) Olga Ivanova Humor and dementia: what can the type of neurodegeneration tell us about pragmatic competence in human language? Session 2 Brain correlates of language processing (5) Jordi Martorell, Simona Mancini, Nicola Molinaro & Manuel Carreiras Oscillatory tracking of syntactic structure and cross-linguistic variation (6) Effrosyni Ntemou, Ann-Katrin Ohlerth, Sebastian Ille, Sandro M. Krie, Roelien Bastiaanse & Adrià Rofes The effect of transitivity on cortical regions involved in action naming: evidence from navigated Transcranial Magnetic Stimulation (7) Monica Vanoncini, Olga Dragoy, Victoria Pozdnyakova & Adrià Rofes The Contribution of the Motor and Auditory Cortex in Priming Action and Sound Verbs: a Pilot Study (8) Roha M. Kaipa Hemispheric Differences in Conflict Sentence Processing in Multilinguals Session 3 Emotions & emotivity in language processing, learning and production (9) Suma Raju & N.P. Nataraja Assessment of verbal fluency skills in Kannada-English speaking bilingual and Kannada speaking monolingual children in the age range of eight to ten years (10) Spandan Chowdhury Emotion Categorization based on Phrase Order Preferences in Bengali (11) Ratul Ghosh An acoustic and neural study of emotions expressed in Bengali speech: A Pilot Study (12) Lucía Sabater, Marta Ponari, Juan Haro, Eva Moreno, Miguel A. -
NLP Resources - Corpora
NLP Resources - Corpora Jun Gong and Daniel Schulman January 25, 2006 1. Organization of Corpora (a) By Media i. Text A. Example: Brown corpus (discussed in class). ii. Speech (with or without transcriptions) A. Example: TIMIT [10] B. Designed for developing speech recognition. C. 630 speakers, each speaking the same 10 sentences. iii. Video (b) By Language i. multilingual parallel corpora (c) By Content [10, 6] i. Many written corpora are news stories. ii. Good spoken collections of conversational speech (Switchboard) (d) By Tagging i. POS Tagging ii. Categorization A. Example: RCV1 and RCV2 [14] B. Large collection of Reuters news stories. C. Hierarchically categorized. D. Used for training and testing text classification systems. iii. Treebanks iv. Annotation Graphs [1] A. Represent all corpus annotations as a directed acyclic graph B. Intented for text, audio, pos, treebanks, etc. 2. Major Resources (a) Linguistic Data Consortium [10] i. Academic/Business consortium, led by UPenn 1 ii. Big collection of corpora, mostly non-free. (b) Evaluation and Language Resources Distribution Agency (ELDA) [6] i. Part of the European Languages Resource Association (ELRA) ii. Mainly multilingual (European languages) corpora (c) International Computer Archive of Modern and Medieval English (ICAME) [7] i. English-only (US, UK, historical, others) ii. Older than other collections (nothing new since 1999?) iii. Includes Brown corpus (d) NIST Collection of Reuters Corpora [14, 12] i. Two large collections (one English, one multilingual) of news stories ii. Manually categorized iii. Free for research use (e) British National Corpus [2] i. Very large (100 million words) and varied (spoken & written) ii. -
The Spoken British National Corpus 2014
The Spoken British National Corpus 2014 Design, compilation and analysis ROBBIE LOVE ESRC Centre for Corpus Approaches to Social Science Department of Linguistics and English Language Lancaster University A thesis submitted to Lancaster University for the degree of Doctor of Philosophy in Linguistics September 2017 Contents Contents ............................................................................................................. i Abstract ............................................................................................................. v Acknowledgements ......................................................................................... vi List of tables .................................................................................................. viii List of figures .................................................................................................... x 1 Introduction ............................................................................................... 1 1.1 Overview .................................................................................................................................... 1 1.2 Research aims & structure ....................................................................................................... 3 2 Literature review ........................................................................................ 6 2.1 Introduction ..............................................................................................................................