- Corpora - ELRA lists

One-year research scholarships
by Valeria Franceschi 16 Nov '22

16 Nov '22

Applications are invited for a 1-year research scholarship in English Linguistics at the Department of Foreign Languages and Literatures, University of Verona, within the project “Interconnected Nord-Est Innovation Ecosystem (iNEST)”, financed by NextGenerationEU in the context of the National Recovery and Resilience Plan (NPRR). The project entails the compilation and analysis of a corpus of English-language texts promoting and describing prominent urban and extra-urban destinations in the Veneto region of Italy as well as the creation of a set of guidelines for tourism promotion. Experience in corpus linguistics, tourism discourse and discourse analysis, among others, are requested from applicants. The closing date for applications is 30th November. For more information about the research project, requirements and application process, you can find the complete call at this link: https://www.univr.it/it/concorsi/assegnisti-di-ricerca/assegni-di-ricerca/0… Best wishes, ---------------------------------------- Valeria Franceschi Temporary Assistant Professor - English Language and Translation (L-LIN/12) Department of Foreign Languages and Literatures University of Verona

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Universal Dependencies, release 2.11
by Dan Zeman 15 Nov '22

15 Nov '22

We are very happy to announce the seventeenth release of annotated treebanks in Universal Dependencies, v2.11, available at http://universaldependencies.org/. Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective (de Marneffe et al., 2021; Nivre et al., 2020). The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008). The general philosophy is to provide a universal inventory of categories and guidelines to facilitate consistent annotation of similar constructions across languages, while allowing language-specific extensions when necessary. The *243* treebanks in v2.11 are annotated according to version 2 of the UD guidelines and represent the following *138 languages:* Abaza, Afrikaans, Akkadian, Akuntsu, Albanian, Amharic, Ancient Greek, Ancient Hebrew, Apurina, Arabic, Armenian, Assyrian, Bambara, Basque, Beja, Belarusian, Bengali, Bhojpuri, Breton, Bulgarian, Buryat, Cantonese, Catalan, Cebuano, Chinese, Chukchi, Classical Chinese, Coptic, Croatian, Czech, Danish, Dutch, English, Erzya, Estonian, Faroese, Finnish, French, Frisian Dutch, Galician, German, Gheg, Gothic, Greek, Guajajara, Guarani, Hebrew, Hindi, Hindi English, Hittite, Hungarian, Icelandic, Indonesian, Irish, Italian, Japanese, Javanese, Kaapor, Kangri, Karelian, Karo, Kazakh, Khunsari, Kiche, Komi Permyak, Komi Zyrian, Korean, Kurmanji, Latin, Latvian, Ligurian, Lithuanian, Livvi, Low Saxon, Madi, Makurap, Malayalam, Maltese, Manx, Marathi, Mbya Guarani, Moksha, Munduruku, Naija, Nayini, Neapolitan, Nheengatu, North Sami, Norwegian, Old Church Slavonic, Old East Slavic, Old French, Old Turkish, Persian, Polish, Pomak, Portuguese, Romanian, Russian, Sanskrit, Scottish Gaelic, Serbian, Sinhala, Skolt Sami, Slovak, Slovenian, Soi, South Levantine Arabic, Spanish, Swedish, Swedish Sign Language, Swiss German, Tagalog, Tamil, Tatar, Teko, Telugu, Thai, Tupinamba, Turkish, Turkish German, Ukrainian, Umbrian, Upper Sorbian, Urdu, Uyghur, Vietnamese, Warlpiri, Welsh, Western Armenian, Western Sierra Puebla Nahuatl, Wolof, Xavante, Xibe, Yakut, Yoruba, Yupik and Zaar. The 138 languages belong to *29 families:* Afro-Asiatic, Arawakan, Arawan, Austro-Asiatic, Austronesian, Basque, Chukotko-Kamchatkan, Code switching, Creole, Dravidian, Eskimo-Aleut, Indo-European, Japanese, Korean, Macro-Je, Mande, Mayan, Mongolic, Niger-Congo, Northwest Caucasian, Pama-Nyungan, Sign Language, Sino-Tibetan, Tai-Kadai, Tungusic, Tupian, Turkic, Uralic and Uto-Aztecan. Depending on the language, the treebanks range in size from less than 1,000 tokens to over 3 million tokens. We expect the next release to be available in May 2023. The size of the following 28 treebanks changed significantly since the last release: Abaza ATB : 0 → 652 Akuntsu TuDeT : 1074 → 1324 Apurina UFPA : 776 → 865 Chinese PatentChar : 0 → 2160 Erzya JR : 17412 → 20541 Estonian EWT : 78331 → 90694 French ParisStories : 30004 → 42865 Gheg GPS : 0 → 15990 Icelandic GC : 0 → 99611 Icelandic Modern : 158150 → 80395 Irish Cadhan : 0 → 3804 Italian ParlaMint : 0 → 20460 Low Saxon LSDC : 2547 → 2935 Makurap TuDeT : 146 → 178 Malayalam UFAL : 0 → 202 Nheengatu CompLin : 0 → 2146 Old East Slavic RNC : 35606 → 48647 Old East Slavic Ruthenian : 0 → 3069 Portuguese CINTIL : 0 → 475860 Portuguese PetroGold : 0 → 250605 Sinhala STB : 0 → 880 Tatar NMCTT : 1458 → 2280 Teko TuDeT : 242 → 1375 Umbrian IKUVINA : 602 → 786 Western Sierra Puebla Nahuatl ITML: 0 → 10120 Xavante XDT : 0 → 120 Yakut YKTDT : 496 → 1403 Zaar Autogramm : 0 → 7625 Daniel Zeman, Joakim Nivre, Mitchell Abrams, Elia Ackermann, Noëmi Aepli, Hamid Aghaei, Željko Agić, Amir Ahmadi, Lars Ahrenberg, Chika Kennedy Ajede, Salih Furkan Akkurt, Gabrielė Aleksandravičiūtė, Ika Alfina, Avner Algom, Chiara Alzetta, Erik Andersen, Lene Antonsen, Katya Aplonova, Angelina Aquino, Carolina Aragon, Glyd Aranes, Maria Jesus Aranzabe, Bilge Nas Arıcan, Þórunn Arnardóttir, Gashaw Arutie, Jessica Naraiswari Arwidarasti, Masayuki Asahara, Katla Ásgeirsdóttir, Deniz Baran Aslan, Cengiz Asmazoğlu, Luma Ateyah, Furkan Atmaca, Mohammed Attia, Aitziber Atutxa, Liesbeth Augustinus, Elena Badmaeva, Keerthana Balasubramani, Miguel Ballesteros, Esha Banerjee, Sebastian Bank, Verginica Barbu Mititelu, Starkaður Barkarson, Rodolfo Basile, Victoria Basmov, Colin Batchelor, John Bauer, Seyyit Talha Bedir, Juan Belieni, Kepa Bengoetxea, Yifat Ben Moshe, Gözde Berk, Yevgeni Berzak, Irshad Ahmad Bhat, Riyaz Ahmad Bhat, Erica Biagetti, Eckhard Bick, Agnė Bielinskienė, Kristín Bjarnadóttir, Rogier Blokland, Victoria Bobicev, Loïc Boizou, Emanuel Borges Völker, Carl Börstell, Cristina Bosco, Gosse Bouma, Sam Bowman, Adriane Boyd, Anouck Braggaar, Kristina Brokaitė, Aljoscha Burchardt, Marie Candito, Bernard Caron, Gauthier Caron, Lauren Cassidy, Maria Clara Castro, Tatiana Cavalcanti, Gülşen Cebiroğlu Eryiğit, Flavio Massimiliano Cecchini, Giuseppe G. A. Celano, Slavomír Čéplö, Neslihan Cesur, Savas Cetin, Özlem Çetinoğlu, Fabricio Chalub, Liyanage Chamila, Shweta Chauhan, Ethan Chi, Taishi Chika, Yongseok Cho, Jinho Choi, Jayeol Chun, Juyeon Chung, Alessandra T. Cignarella, Silvie Cinková, Aurélie Collomb, Çağrı Çöltekin, Miriam Connor, Daniela Corbetta, Marine Courtin, Mihaela Cristescu, Philemon Daniel, Elizabeth Davidson, Leonel Figueiredo de Alencar, Mathieu Dehouck, Martina de Laurentiis, Marie-Catherine de Marneffe, Valeria de Paiva, Mehmet Oguz Derin, Elvis de Souza, Arantza Diaz de Ilarraza, Carly Dickerson, Arawinda Dinakaramani, Elisa Di Nuovo, Bamba Dione, Peter Dirix, Kaja Dobrovoljc, Timothy Dozat, Kira Droganova, Puneet Dwivedi, Christian Ebert, Hanne Eckhoff, Sandra Eiche, Marhaba Eli, Ali Elkahky, Binyam Ephrem, Olga Erina, Tomaž Erjavec, Aline Etienne, Wograine Evelyn, Sidney Facundes, Richárd Farkas, Federica Favero, Jannatul Ferdaousi, Marília Fernanda, Hector Fernandez Alcalde, Jennifer Foster, Cláudia Freitas, Kazunori Fujita, Katarína Gajdošová, Daniel Galbraith, Federica Gamba, Marcos Garcia, Moa Gärdenfors, Sebastian Garza, Fabrício Ferraz Gerardi, Kim Gerdes, Filip Ginter, Gustavo Godoy, Iakes Goenaga, Koldo Gojenola, Memduh Gökırmak, Yoav Goldberg, Xavier Gómez Guinovart, Berta González Saavedra, Bernadeta Griciūtė, Matias Grioni, Loïc Grobol, Normunds Grūzītis, Bruno Guillaume, Céline Guillot-Barbance, Tunga Güngör, Nizar Habash, Hinrik Hafsteinsson, Jan Hajič, Jan Hajič jr., Mika Hämäläinen, Linh Hà Mỹ, Na-Rae Han, Muhammad Yudistira Hanifmuti, Takahiro Harada, Sam Hardwick, Kim Harris, Dag Haug, Johannes Heinecke, Oliver Hellwig, Felix Hennig, Barbora Hladká, Jaroslava Hlaváčová, Florinel Hociung, Petter Hohle, Marivel Huerta Mendez, Jena Hwang, Takumi Ikeda, Anton Karl Ingason, Radu Ion, Elena Irimia, Ọlájídé Ishola, Artan Islamaj, Kaoru Ito, Siratun Jannat, Tomáš Jelínek, Apoorva Jha, Katharine Jiang, Anders Johannsen, Hildur Jónsdóttir, Fredrik Jørgensen, Markus Juutinen, Hüner Kaşıkara, Andre Kaasen, Nadezhda Kabaeva, Sylvain Kahane, Hiroshi Kanayama, Jenna Kanerva, Neslihan Kara, Ritván Karahóǧa, Boris Katz, Tolga Kayadelen, Sarveswaran Kengatharaiyer, Jessica Kenney, Václava Kettnerová, Jesse Kirchner, Elena Klementieva, Elena Klyachko, Arne Köhn, Abdullatif Köksal, Kamil Kopacewicz, Timo Korkiakangas, Mehmet Köse, Alexey Koshevoy, Natalia Kotsyba, Jolanta Kovalevskaitė, Simon Krek, Parameswari Krishnamurthy, Sandra Kübler, Adrian Kuqi, Oğuzhan Kuyrukçu, Aslı Kuzgun, Sookyoung Kwak, Veronika Laippala, Lucia Lam, Lorenzo Lambertino, Tatiana Lando, Septina Dian Larasati, Alexei Lavrentiev, John Lee, Phương Lê Hồng, Alessandro Lenci, Saran Lertpradit, Herman Leung, Maria Levina, Cheuk Ying Li, Josie Li, Keying Li, Yixuan Li, Yuan Li, KyungTae Lim, Bruna Lima Padovani, Krister Lindén, Nikola Ljubešić, Olga Loginova, Stefano Lusito, Andry Luthfi, Mikko Luukko, Olga Lyashevskaya, Teresa Lynn, Vivien Macketanz, Menel Mahamdi, Jean Maillard, Ilya Makarchuk, Aibek Makazhanov, Michael Mandl, Christopher Manning, Ruli Manurung, Büşra Marşan, Cătălina Mărănduc, David Mareček, Katrin Marheinecke, Stella Markantonatou, Héctor Martínez Alonso, Lorena Martín Rodríguez, André Martins, Jan Mašek, Hiroshi Matsuda, Yuji Matsumoto, Alessandro Mazzei, Ryan McDonald, Sarah McGuinness, Gustavo Mendonça, Tatiana Merzhevich, Niko Miekka, Karina Mischenkova, Margarita Misirpashayeva, Anna Missilä, Cătălin Mititelu, Maria Mitrofan, Yusuke Miyao, AmirHossein Mojiri Foroushani, Judit Molnár, Amirsaeid Moloodi, Simonetta Montemagni, Amir More, Laura Moreno Romero, Giovanni Moretti, Keiko Sophie Mori, Shinsuke Mori, Tomohiko Morioka, Shigeki Moro, Bjartur Mortensen, Bohdan Moskalevskyi, Kadri Muischnek, Robert Munro, Yugo Murawaki, Kaili Müürisep, Pinkey Nainwani, Mariam Nakhlé, Juan Ignacio Navarro Horñiacek, Anna Nedoluzhko, Gunta Nešpore-Bērzkalne, Manuela Nevaci, Lương Nguyễn Thị, Huyền Nguyễn Thị Minh, Yoshihiro Nikaido, Vitaly Nikolaev, Rattima Nitisaroj, Alireza Nourian, Hanna Nurmi, Stina Ojala, Atul Kr. Ojha, Hulda Óladóttir, Adédayọ̀ Olúòkun, Mai Omura, Emeka Onwuegbuzia, Noam Ordan, Petya Osenova, Robert Östling, Lilja Øvrelid, Şaziye Betül Özateş, Betül Özateş, Merve Özçelik, Arzucan Özgür, Balkız Öztürk Başaran, Teresa Paccosi, Alessio Palmero Aprosio, Anastasia Panova, Hyunji Hayley Park, Niko Partanen, Elena Pascual, Marco Passarotti, Agnieszka Patejuk, Guilherme Paulino-Passos, Giulia Pedonese, Angelika Peljak-Łapińska, Siyao Peng, Cenel-Augusto Perez, Natalia Perkova, Guy Perrier, Slav Petrov, Daria Petrova, Andrea Peverelli, Jason Phelan, Jussi Piitulainen, Rodrigo Pintucci, Tommi A Pirinen, Emily Pitler, Magdalena Plamada, Barbara Plank, Thierry Poibeau, Larisa Ponomareva, Martin Popel, Lauma Pretkalniņa, Sophie Prévost, Prokopis Prokopidis, Adam Przepiórkowski, Robert Pugh, Tiina Puolakainen, Sampo Pyysalo, Peng Qi, Andriela Rääbis, Alexandre Rademaker, Mizanur Rahoman, Taraka Rama, Loganathan Ramasamy, Carlos Ramisch, Fam Rashel, Mohammad Sadegh Rasooli, Vinit Ravishankar, Livy Real, Petru Rebeja, Siva Reddy, Mathilde Regnault, Georg Rehm, Ivan Riabov, Michael Rießler, Erika Rimkutė, Larissa Rinaldi, Laura Rituma, Putri Rizqiyah, Luisa Rocha, Eiríkur Rögnvaldsson, Ivan Roksandic, Mykhailo Romanenko, Rudolf Rosa, Valentin Roșca, Davide Rovati, Ben Rozonoyer, Olga Rudina, Jack Rueter, Kristján Rúnarsson, Shoval Sadde, Pegah Safari, Benoît Sagot, Aleksi Sahala, Shadi Saleh, Alessio Salomoni, Tanja Samardžić, Stephanie Samson, Manuela Sanguinetti, Ezgi Sanıyar, Dage Särg, Marta Sartor, Mitsuya Sasaki, Baiba Saulīte, Yanin Sawanakunanon, Shefali Saxena, Kevin Scannell, Salvatore Scarlata, Nathan Schneider, Sebastian Schuster, Lane Schwartz, Djamé Seddah, Wolfgang Seeker, Mojgan Seraji, Syeda Shahzadi, Mo Shen, Atsuko Shimada, Hiroyuki Shirasu, Yana Shishkina, Muh Shohibussirri, Maria Shvedova, Janine Siewert, Einar Freyr Sigurðsson, João Ricardo Silva, Aline Silveira, Natalia Silveira, Maria Simi, Radu Simionescu, Katalin Simkó, Mária Šimková, Haukur Barri Símonarson, Kiril Simov, Dmitri Sitchinava, Maria Skachedubova, Aaron Smith, Isabela Soares-Bastos, Barbara Sonnenhauser, Shafi Sourov, Carolyn Spadine, Rachele Sprugnoli, Vivian Stamou, Steinþór Steingrímsson, Antonio Stella, Abishek Stephen, Milan Straka, Emmett Strickland, Jana Strnadová, Alane Suhr, Yogi Lesmana Sulestio, Umut Sulubacak, Shingo Suzuki, Daniel Swanson, Zsolt Szántó, Chihiro Taguchi, Dima Taji, Yuta Takahashi, Fabio Tamburini, Mary Ann C. Tan, Takaaki Tanaka, Dipta Tanaya, Mirko Tavoni, Samson Tella, Isabelle Tellier, Marinella Testori, Guillaume Thomas, Sara Tonelli, Liisi Torga, Marsida Toska, Trond Trosterud, Anna Trukhina, Reut Tsarfaty, Utku Türk, Francis Tyers, Sveinbjörn Þórðarson, Vilhjálmur Þorsteinsson, Sumire Uematsu, Roman Untilov, Zdeňka Urešová, Larraitz Uria, Hans Uszkoreit, Andrius Utka, Elena Vagnoni, Sowmya Vajjala, Rob van der Goot, Martine Vanhove, Daniel van Niekerk, Gertjan van Noord, Viktor Varga, Uliana Vedenina, Giulia Venturi, Eric Villemonte de la Clergerie, Veronika Vincze, Natalia Vlasova, Aya Wakasa, Joel C. Wallenberg, Lars Wallin, Abigail Walsh, Jing Xian Wang, Jonathan North Washington, Maximilan Wendt, Paul Widmer, Shira Wigderson, Sri Hartati Wijono, Vanessa Berwanger Wille, Seyi Williams, Mats Wirén, Christian Wittern, Tsegay Woldemariam, Tak-sum Wong, Alina Wróblewska, Mary Yako, Kayo Yamashita, Naoki Yamazaki, Chunxiao Yan, Koichi Yasuoka, Marat M. Yavrumyan, Arife Betül Yenice, Olcay Taner Yıldız, Zhuoran Yu, Arlisa Yuliawati, Zdeněk Žabokrtský, Shorouq Zahra, Amir Zeldes, He Zhou, Hanzhi Zhu, Anna Zhuravleva, Rayan Ziane References Marie-Catherine de Marneffe, Christopher Manning, Joakim Nivre, Daniel Zeman. 2021. Universal Dependencies. In Computational Linguistics 47:2, pp. 255–308. Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, Jan Hajič, Christopher D. Manning, Sampo Pyysalo, Sebastian Schuster, Francis Tyers, Daniel Zeman. 2020. Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection. In Proceedings of LREC. -------------------------------------------------------------------------------- Marie-Catherine de Marneffe, Bill MacCartney, and Christopher D. Manning. 2006. Generating typed dependency parses from phrase structure parses. In Proceedings of LREC. Marie-Catherine de Marneffe and Christopher D. Manning. 2008. The Stanford typed dependencies representation. In COLING Workshop on Cross-framework and Cross-domain Parser Evaluation. Marie-Catherine de Marneffe, Timothy Dozat, Natalia Silveira, Katri Haverinen, Filip Ginter, Joakim Nivre, and Christopher Manning. 2014. Universal Stanford Dependencies: A cross-linguistic typology. In Proceedings of LREC. Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, Yoav Goldberg, Jan Hajič, Christopher D. Manning, Ryan McDonald, Slav Petrov, Sampo Pyysalo, Natalia Silveira, Reut Tsarfaty, Daniel Zeman. 2016. Universal Dependencies v1: A Multilingual Treebank Collection. In Proceedings of LREC. Slav Petrov, Dipanjan Das, and Ryan McDonald. 2012. A universal part-of-speech tagset. In Proceedings of LREC. Daniel Zeman. 2008. Reusable Tagset Conversion Using Tagset Drivers. In Proceedings of LREC.

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November 2022 Newsletter - LDC
by Penn LDC 15 Nov '22

15 Nov '22

In this newsletter: Join LDC for membership year 2023 Fall 2022 data scholarship recipients Spring 2023 data scholarship application deadline 30th Anniversary Highlight: CALLFRIEND New publications: BOLT English Translation Treebank - Egyptian Arabic SMS/Chat<https://catalog.ldc.upenn.edu/LDC2022T06> Samrómur Children Icelandic Speech 1.0<https://catalog.ldc.upenn.edu/LDC2022S11> Third DIHARD Challenge Development<https://catalog.ldc.upenn.edu/LDC2022S12> ________________________________ Join LDC for membership year 2023 It's time to renew your LDC membership for 2023. Current (2022) members who renew their membership before March 1, 2023 will receive a 10% discount. New or returning organizations will receive a 5% discount if they join the Consortium by March 1. In addition to receiving new publications, current LDC members enjoy the benefit of licensing older data from our Catalog of 900+ holdings at reduced fees. Current-year for-profit members may use most data for commercial applications. Plans for 2023 publications are in progress. Among the expected releases are: * AIDA Ukrainian Broadcast and Telephone Speech Audio and Transcripts: 156 hours of Ukrainian conversational telephone speech and broadcast news with 1.2 million words of corresponding orthographic transcripts * 2019 NIST SRE: audiovisual and leaderboard challenge sets based on amateur videos and Tunisian Arabic telephone speech, respectively * DEFT English ERE: English text from assorted genres annotated for entities, relations and events * Mixer 3 and Mixer 7 speech collections: thousands of hours of telephone speech and metadata from Mixer 3 (multiple languages) and Mixer 7 (Spanish, plus interviews and transcript readings) * CALLFRIEND Russian: 100 telephone conversations among native speakers, transcripts and a lexicon, released in separate speech and text data sets * REMIX Telephone Collection: English telephone speech from 385 participants in previous Mixer studies * LORELEI: representative and incident language packs containing monolingual text, bi-text, translations, annotations, supplemental resources and related tools in various languages (e.g., Indonesian, Swahili, Tagalog, Tamil, Zulu) For full descriptions of all LDC data sets, browse our Catalog<https://catalog.ldc.upenn.edu/>. Visit Join LDC<https://www.ldc.upenn.edu/members/join-ldc> for details on membership, user accounts and payment. Fall 2022 LDC data scholarship recipients LDC congratulates the following Fall 2022 data scholarship recipients: * Nelson Filipe Costa: Concordia University (Canada); PhD, Machine Learning. Nelson is awarded a copy of Penn Discourse Treebank Version 3.0 (LDC2019T05<https://catalog.ldc.upenn.edu/LDC2019T05>) for his work in discourse relationships and mapping. * Paul Pope: University of Eastern Finland (Finland); MA, Linguistic Data Sciences. Paul is awarded a copy of ETS Corpus of Non-Native Written English (LDC2014T06<https://catalog.ldc.upenn.edu/LDC2014T06>) for his research on text classification. * Abhinav Singh: Sharda University (India); PhD, Forensic Science. Abhinav is awarded a copy of TIMIT Acoustic-Phonetic Continuous Speech Corpus (LDC93S1<https://catalog.ldc.upenn.edu/LDC93S1>) for his research on forensic speech recognition. * Lucas Zheng: Deerfield Academy (USA); High School Scholar. Lucas is awarded copies of Arabic Treebank Part 1 v. 4.1 (LDC2010T13<https://catalog.ldc.upenn.edu/LDC2010T13>) and Arabic Treebank Part 2 v. 3.1 (LDC2011T09<https://catalog.ldc.upenn.edu/LDC2011T09>) for his work on analyzing syntactic and lexical similarities across MSA genres and POS-tagging for MSA. Students can learn more about the LDC data scholarship program on the Data Scholarships page.<https://www.ldc.upenn.edu/language-resources/data/data-scholarships> Spring 2023 data scholarship application deadline Applications are now being accepted through January 15, 2023 for the Spring 2023 LDC data scholarship program which provides university students with no-cost access to LDC data. Consult the LDC Data Scholarship<https://www.ldc.upenn.edu/language-resources/data/data-scholarships>s page for more information about program rules and submission requirements. 30th Anniversary Highlight: CALLFRIEND The CALLFRIEND series is a multi-language collection of unscripted telephone conversations conducted by LDC in the 1990s to support language identification technology development (Liberman & Cieri, 1998<https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/lrec1998-creation-d…>). Covered languages are American English, Canadian French, Egyptian Arabic, Farsi, German, Hindi, Japanese, Korean, Mandarin Chinese, Spanish, Tamil and Vietnamese. For English, Mandarin and Spanish, the collection includes two distinct dialects. Participants could speak with a person of their choice on any topic; most called family members and friends. All calls originated in North America. This speech data was the foundation for NIST's Language Recognition Evaluations<https://www.nist.gov/itl/iad/mig/language-recognition> conducted from 1996-2007. The first editions of the CALLFRIEND series published in LDC's Catalog in 1996 contain 60 calls evenly split into 20 calls each for a training partition to develop language models, a development partition for parameter tuning, and an evaluation partition to test performance (Torres-Carrasquillo, et al., 2004<https://www.isca-speech.org/archive_open/archive_papers/odyssey_04/ody4_297…>). Beginning in 2014, LDC released second editions for American English (LDC2019S21<https://catalog.ldc.upenn.edu/LDC2019S21>, LDC2020S08<https://catalog.ldc.upenn.edu/LDC2020S08>), Canadian French (LDC2019S18<https://catalog.ldc.upenn.edu/LDC2019S18>), Egyptian Arabic (LDC2019S04<https://catalog.ldc.upenn.edu/LDC2019S04>), Farsi (LDC2014S01<https://catalog.ldc.upenn.edu/LDC2014S01>), and Mandarin Chinese (LDC2018S09<https://catalog.ldc.upenn.edu/LDC2018S09>, LDC2020S06<https://catalog.ldc.upenn.edu/LDC2020S06>). The goal of the second editions is to facilitate continued widespread use of the data, specifically, by updating the audio files to .wav format, simplifying the directory structure, adding documentation and metadata, and combining the training, development and evaluation splits. CALLFRIEND Farsi Second Edition also includes additional telephone recordings and a separate transcripts release (LDC2014T01<https://catalog.ldc.upenn.edu/LDC2014T01>). In addition to work on language identification, CALLFRIEND corpora have been used in a variety of research tasks, including subject omission in Korean (Lee 2012<https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE10893918>), contemporary Persian vowels in casual speech (Jones 2019<https://repository.upenn.edu/pwpl/vol25/iss1/15/>), Mandarin telephone closings among familiars (Huang, 2020<https://www.jbe-platform.com/content/journals/10.1075/ap.19017.hua>), and adjective constructions in English conversation (Bybee & Thompson, 2021<https://www.mdpi.com/2226-471X/7/1/2/htm>), among many others. To learn more about the CALLFRIEND collection or about other LDC corpora used for language identification research, search the Catalog<https://catalog.ldc.upenn.edu/search> by the "recommended application" and select "language identification" from the list. ________________________________ New publications: BOLT English Translation Treebank - Egyptian Arabic SMS/Chat<https://catalog.ldc.upenn.edu/LDC2022T06> was developed by LDC and consists of SMS and chat text data (472 files representing 98,206 tokens) translated from Egyptian Arabic to English and annotated for part-of-speech and syntactic structure. Only the translated English text is included in the source data for this release. Part-of-speech and treebank annotation conformed to Penn Treebank II style, incorporating changes to those guidelines that were developed under the GALE (Global Autonomous Language Exploitation) program. Supplementary guidelines for English treebanks and web text are included in the corpus documentation. 2022 members can access this corpus through their LDC accounts. Non-members may license this data for a fee. * Samrómur Children Icelandic Speech 1.0<https://catalog.ldc.upenn.edu/LDC2022S11> was developed by the Language and Voice Lab, Reykjavik University<https://lvl.ru.is/> in cooperation with Almannarómur, Center for Language Technology<https://almannaromur.is/>. The corpus contains 131 hours of Icelandic prompted speech from 3,175 speakers (children, aged 4-17 years) representing 137,597 utterances. Speech data was collected between October 2019 and September 2021 using the Samrómur website<https://samromur.is> which displayed prompts to participants. The prompts were mainly from The Icelandic Gigaword Corpus<http://clarin.is/en/resources/gigaword>, which includes text from novels, news, plays, and from a list of location names in Iceland. Additional prompts were taken from the Icelandic Web of Science<https://www.visindavefur.is/> and others were created by combining a name followed by a question or a demand. Prompts and speaker metadata are included in the corpus 2022 members can access this corpus through their LDC accounts provided they have submitted a completed copy of the special license agreement. Non-members may license this data for a fee. * Third DIHARD Challenge Development<https://catalog.ldc.upenn.edu/LDC2022S12> was developed by LDC and contains approximately 34 hours of English and Chinese speech data along with corresponding annotations used in support of the Third DIHARD Challenge<https://dihardchallenge.github.io/dihard3>. The DIHARD third development and evaluation sets were drawn from diverse sources including monologues, map task dialogues, broadcast interviews, sociolinguistic interviews, meeting speech, speech in restaurants, clinical recordings, and amateur web videos. Annotations include diarization and segmentation. 2022 members can access this corpus through their LDC accounts. Non-members may license this data for a fee. To unsubscribe from this newsletter, log in to your LDC account<https://catalog.ldc.upenn.edu/login> and uncheck the box next to "Receive Newsletter" under Account Options; or contact LDC for assistance.

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Research Assistant for Voice- and Chatbots at TU Berlin
by Roland Roller 15 Nov '22

15 Nov '22

The Quality and Usability Group at Technical University Berlin is searching for a research assistant working on spoken and text-based interactive dialog-systems. Further information about the position can be found here: https://tub.stellenticket.de/en/offers/157021/ If you have got questions about the position, please contact my colleague Stefan Hillman (stefan.hillmann(a)tu-berlin.de). The closing date is the 5th of December 2022.

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CfP ICAME44
by Bertus van Rooy 15 Nov '22

15 Nov '22

The 44th annual conference of the International Computer Archive of Modern and Medieval English (ICAME44) is hosted by the North-West University in Vanderbijlpark, South Africa, from 17 to 21 May 2023. The conference format will be hybrid, with on-site and on-line participation possible. The conference theme is “English going places, Corpora crossing spaces”. Participants are invited to reflect on how the diffusion of English across spaces – physical, virtual or metaphorical – contributes to shape the language. Confirmed keynote speakers are: Alexandra Esimaje (Benson Idahosa University, Nigeria) “Challenges of doing corpus linguistics in Africa” Haidee Kotze (Utrecht University, The Netherlands) “Protean invisibilities: A corpus-based perspective on the role of translation in language variation and change in global Englishes” Christiane Meierkord (Ruhr University Bochum, Germany) “Corpora crossing disciplinary borders: ICE Uganda meets sociolinguistics, anthropology and ethnography” Mike Scott (Lexical Analysis Software & Aston University, United Kingdom) “News Downloads and Text Coverage: Case Studies in Relevance” Submission Guidelines All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome: Full papers (20 minutes presentation,10 minutes discussion) describing the findings of new research projects involving the study of the English language by means of corpora. Work-in-Progress reports (10 minutes presentation, 5 minutes discussion) describing ongoing projects prior to final results. Posters describing new ideas or new findings. When submitting your abstract, please indicate in the title line whether you wish to be considered for a full paper, WiP report or poster. Please submit your abstract via EasyChair at https://easychair.org/conferences/?conf=icame44 The submission deadline for early review (before Christmas) is 2 December 2022, and otherwise 23 December 2022 for review done by end of January 2023. Venue The conference will be held in Vanderbijlpark, South Africa, at the Emerald Resort. The resort simultaneously provides the venue and accommodation. It is about 95km away from OR Tambo International Airport in Johannesburg. Transport from the airport be arranged to conference attendees who require it on the two days prior to the conference, and back to the airport after the completion of the conference, as there are no direct public transport options linking the airport and Vanderbijlpark. There is a direct connection by highway, for attendees who want to rent a vehicle or book a taxi/Uber in the alternative. Contact All questions about submissions or the conference should be emailed to the conference organiser, Bertus van Rooy, using e-mail address a.j.vanrooy [at] uva.nl. More information is also available on the conference website - ICAME44 | humanities.nwu.ac.za - but it is continuously being updated with further information.

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Call-for-workshop-proposals: ACM ICMR 2023
by Bogdan Ionescu 15 Nov '22

15 Nov '22

[Apologies for multiple postings] ACM International Conference on Multimedia Retrieval 2023 Thessaloniki, Greece, 12-15 June 2023 https://icmr2023.org/ *** Call for Workshop Proposals *** The ACM International Conference on Multimedia Retrieval in 2023 (ICMR 2023) is calling for high quality Workshops addressing innovative research in multimedia retrieval and its related broad fields. The scope of the conference is not limited to search and retrieval of multimedia data but also addresses analysis and understanding of multimedia contents, including: - Integration of diverse multimodal data. - Deep learning-based methodology and practical multimedia applications. - Multimedia dataset creation and management (and compliance with ethical practices). - Interpretability of multimedia analysis and retrieval techniques and connection with social sciences. - Exploring bias in multimedia datasets. - Practical systems/applications of multimedia analysis and retrieval on different areas, e.g., media & entertainment, culture, health, security, etc. - Multimedia analysis and retrieval aiming to solve major societal challenges (e.g., disinformation, climate change, social inequalities etc.). - Legal/ethical challenges and societal impact of multimedia analysis and retrieval. - Community-contributed social data. - Lifelogging data and automatically generated sensor data. The Workshops will contain both: - Long research papers which should present complete work with evaluations on topics related to the Conference. They will have both oral and poster presentations at the conference. - Short research papers which should present preliminary results or more focused contributions. They will be presented as posters at the conference. *** Important Dates *** Submit your workshop proposal until December 15, 2022. *** Submission Instructions *** Please, download the Workshop Proposal template from the conference website. Please, send your proposal as a pdf file to the Workshops Chairs at icmr2023-workshops(a)iti.gr. *** Contact *** For any question regarding submissions for workshop proposals, please visit the conference website or email the Workshops Chairs (icmr2023-workshops(a)iti.gr). *** Workshops Chairs *** Dr. Ichiro Ide (Nagoya University) Prof. Lucile Sassatelli (Université Côte d’Azur) Prof. Ioannis (Yiannis) Patras (Queen Mary University of London) Dr. Filareti Tsalakanidou (Centre for Research and Technology Hellas) On behalf of the organizers, Bogdan Ionescu https://www.aimultimedialab.ro/

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Erinnerung: Förderung einer Open-Access-Publikation „Einführung in die Computerlinguistik“ (Deadline 15.12.2022)
by josef Ruppenhofer 14 Nov '22

14 Nov '22

(Apologies if you end up receiving this multiple times. The text below appears only in German as it concerns a call for a German language book proposal.) Aufforderung zur Konzepteinreichung Zum Hintergrund Das letzte Jahrzehnt hat weltweit zahlreiche neue Aktivitäten und Entwicklungen auf dem Feld der Computerlinguistik erbracht. Nicht nur haben sich neue Ansätze und Methoden durchgesetzt; die Computerlinguistik als solche hat sich auch disziplinär stark ausdifferenziert. Dessen ungeachtet ist festzustellen, dass für Forschung und Lehre kein aktuelles deutschsprachiges Lehrbuch zur Verfügung steht, das ein umfassendes Bild des aktuellen Standes der Computerlinguistik zu zeichnen vermag. Die GSCL möchte deshalb dazu beitragen, diese Lücke zu füllen und hat beschlossen, Mittel zur Veröffentlichung eines umfassenden einführenden Lehrbuches oder einander ergänzender Lehrbücher zur Verfügung stellen. Was wird gefördert? Die Einführung soll sich vorrangig an den wissenschaftlichen Nachwuchs, insbesondere an Studierende in einem Bachelor-Studiengang, richten. Diese allgemeine Einführung in den Forschungsgegenstand sollte zudem die Trends der letzten Jahre thematisieren. Der Fokus der Publikation oder der Publikationen könnte beispielsweise auf anwendungsorientierte Fragestellungen der Informatik gelegt werden. Alternativ könnten auch Schwerpunktsetzungen in den Bereichen Linguistik oder Digital Humanities erfolgen. Die GSCL wird die finanziellen Mittel bereitstellen, die zur Deckung der Publikationskosten eines oder mehrerer sich ergänzender deutschsprachiger Open- Access-Bände zur Einführung in die Computerlinguistik in einem renommierten Verlag benötigt werden. Sofern die Autorinnen und Autoren bzw. Herausgeberinnen und Herausgeber die Publikation bei einem kostenfreien Non-Profit-Verlag bevorzugen, unterstützt die GSCL auch solche Vorhaben, kann die dadurch freiwerdenden finanziellen Mittel allerdings nicht umwidmen. Momentan steht die GSCL mit renommierten Verlagen in Kontakt, die Autorinnen und Autoren nicht nur ein breitgefächertes Distributionsnetz, sondern auch deutliche Mehrwerte für die Sichtbarkeit und Reichweite ihrer Forschung bieten. Die Einführung soll so konzipiert werden, dass sie sowohl in digitaler Fassung als PDF über Bibliotheken und Gedächtnisorganisationen barrierefrei zur Verfügung steht, als auch als Druckversion über den Buchhandel verbreitet und von Bibliotheken angeschafft werden kann. Die GSCL wird alle mit der Publikation anfallenden Kosten von professionellem Lektorat, Satz und dauerhafter Bereitstellung des Bandes übernehmen. Es steht zu erwarten, dass ein Zuschlag für die erfolgreichen Autorinnen und Autoren erhebliche Reputationsgewinne infolge der Schließung einer Lücke in der deutschsprachigen Computerlinguistik zur Folge haben wird. Weitere Anreize, insbesondere Honorare für das Verfassen von Texten oder die Herausgabe des Bandes werden von der GSCL explizit nicht ausgelobt. Zur Antragstellung Die GSCL bittet einschlägig erfahrene Wissenschaftlerinnen und Wissenschaftler um Einreichung eines Essays zur thematischen Ausrichtung einer Einführung. Die Einführung kann sowohl als monographische Schrift als auch als Sammelband konzipiert werden. Bis zum 15.12.2022 sind Autorinnen und Autoren oder Herausgeberinnen und Herausgeber aufgerufen, eine entsprechende kurze Konzeption einzureichen, welche die thematische Ausrichtung des Lehrbuches konzise skizziert und, im Falle von Sammelbänden, Einzelthemen und potenzielle Autorinnen und Autoren aufführt. Erwartet wird überdies ein straffer, aber umsetzbarer Zeitplan zur Durchführung der Publikation, die idealerweise innerhalb eines Jahres abzuschließen sein wird. Die Auswahl der Einreichungen wird bis zum 31.01.2023 erfolgen; entsprechende Vorschläge sind bitte unter dem Betreff „GSCL: Einführung in die Computerlinguistik“ an die Adresse informationsreferent(a)gscl.org zu richten

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Internship offer at INRIA
by Biswesh Mohapatra 14 Nov '22

14 Nov '22

Hello Everyone, I would like to inform you that our team [ http://articulab.hcii.cs.cmu.edu/ | Articulab ] at INRIA Paris is having an internship position for working on understanding pre-trained dialog models. PFA a description of the internship. Ideally, the candidate would start working in January 2023. Warm Regards, Biswesh Mohapatra INRIA

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Call for papers: Explainable AI in Natural Language Processing
by Somnath Banerjee 14 Nov '22

14 Nov '22

*** Apologies for cross-posting *** Call for papers: Explainable AI in Natural Language Processing Traditional Natural Language Processing (NLP) models (e.g., decision trees, Markov models, etc.) have primarily been based on techniques that are inherently interpretable models, referred to as white-box techniques. However, in recent years, NLP models have employed advanced neural approaches along with language embedding features. Using these advanced approaches, mostly referred to as black-box techniques, the NLP models have yielded state-of-art performance. Nonetheless, the level of interpretability (e.g., how the model arrives at its results) has reduced significantly. This obfuscated interpretability not only lowers the end users’ trust in the NLP models but also makes it challenging for the developers to debug or improve by analyzing the models for further improvement. Therefore, nowadays, researchers in the NLP community are giving significant attention to the emerging field called Explainable AI (XAI) to tackle the obfuscated complexity of AI systems for trust and improvement. Apart from academia, organizations and companies also have launched high-funding projects such as DARPA XAI, People +AI Research (PAIR), etc. As XAI is still a growing field, there is plenty of room for innovation to improve the explainability of NLP systems. In recent works, explainable NLP models have captured linguistic knowledge of neural networks, explain predictions, stress-test models via challenge sets or adversarial examples, and interpret language embeddings. The goal of this Research Topic is to better understand the present status of the XAI in NLP by identifying: new dimensions for a better explanation, evaluation techniques used to measure the quality of explanations, approaches or developments of new software toolkits to explain XAI in NLP, and transparent deep learning models for different NLP task. The scope of this Research Topic covers (but is not restricted to) the following topics: • Survey of XAI in NLP in general or any particular NLP task such as NER, QA, Sentiment analysis, social media (SocialNLP), etc. • Explainable Neural models in Machine Translation • Explainable Neural models in Named Entity Recognition • Explainable Neural models in Question Answering • Explainable Neural models in Sentiment Analysis • Explainable Neural models in Opinion Mining • Explainable Neural models in SocialNLP • Evaluation techniques used to measure the quality of explanations • Tools for explaining explainability • Resources related to XAI in the context of NLP The Research Topic welcomes contributions toward interpretable models for efficient solutions to NLP research problems that explain the explainability of the proposed model using suitable explainability technique(s) (e.g., example-driven, provenance, feature importance, induction, surrogate models, etc.), visualization technique(s) (e.g., raw examples, saliency, raw declarative, etc.), and other aspects. Software toolkits or approaches that can help users express explainability to their models and ML pipelines are also welcome. The full Call for Papers is available at https://www.frontiersin.org/research-topics/48440/explainable-ai-in-natural… Impact of the publication: https://www.frontiersin.org/about/impact The current deadlines are: * Abstract Deadline:16 December 2022 - A soft-deadline, thus whilst not mandatory, if you would like feedback on your prospective manuscript’s suitability, I encourage you to submit an abstract around this time. * Manuscript Deadline: 14 April 2023, This is a mandatory deadline for your full manuscript submission. However, we can accommodate personal extensions on a case-by-case basis. Guest Editors: Somnath Banerjee (University of Tartu, somnath.banerjee(a)ut.ee) David Tomás (University of Alicante, dtomas(a)dlsi.ua.es) Somnath Banerjee Lecturer, Institute of Computer Science, University of Tartu, Narva mnt 18, room 3063 51009 Tartu, ESTONIA webpage: http://www.ut.ee//~somnath/

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PhD Thesis defense: Benjamin Muller (Inria Paris, Almanach) 17/11/2022 8h30 "How Can We Make Language Models Better at Handling the Diversity and Variability of Natural Languages?"
by Djamé Seddah 14 Nov '22

14 Nov '22

Hi everyone, I have the pleasure to invite you to my Ph.D. defense next Thursday at 8:30 AM Paris time, it will take place at the Inria Paris Research Centre (2 rue Simone Iff, 75012 Paris) at the Jacques-Louis Lions room. It will be followed by a pot de thèse around 11 am. The Ph.D. committee will be made of: • Yoav Golberg, Bar Ilan University, Rapporteur • ‪Lilja Øvrelid, University of Oslo, Rapportrice • Benjamin Piwowarski, CNRS, Examinateur • Benoît Sagot INRIA Paris, Directeur • Natalie Schulter, IT University of Copenhagen, Examinatrice • Djamé Seddah, INRIA Paris, Superviseur Abstract: Deep Learning techniques applied to Natural Language Processing (NLP) have led to impressive empirical progress in recent years. In essence, this progress is due to the development of better-contextualized representations of textual data that can be easily used --- or transferred --- for a wide variety of NLP tasks. In their most recent and popular forms, these models consist of large-scale deep-learning language models, first pretrained on a large quantity of raw data and then adapted to specific tasks. These language models are now essential for search engines, question-answering pipelines, machine translation systems, etc. However, these models usually require substantial computing power and large amounts of raw textual data. This makes natural language's inherent diversity and variability a vivid challenge in NLP. Indeed, collecting large datasets for low-resource languages is challenging and costly, and training models from scratch for every domain and language is unreasonable in practice. Additionally, understanding the behavior of deep learning-based models is intrinsically tricky, making the development of more cost-effective techniques even more challenging. For these reasons, we focus on the following question: ``How can we make language models better at handling the variability and diversity of natural languages?''. As a starting step, we explore the generalizability of language models by building one of the first large-scale replication of a BERT model for a non-English language. We analyze the critical training ingredients and show that it can achieve state-of-the-art performance with only a few gigabytes of diverse data. Our results raise the question of using these language models on highly-variable domains such as these found in user-generated content. Focusing on domain-gap reduction via lexical normalization, we show that this task can be addressed accurately with BERT-like models. However, we show that it only partially helps downstream performance. In consequence, we focus on direct adaptation techniques using what we refer to as representation transfer and explore challenging settings such as the zero-shot setting, low-resource language varieties like Bambara or Uyghur, and highly variable and non-standardized code-mixed dialects such as a North-African Arabic dialect written in the Latin script. We show that multilingual language models can be adapted and used efficiently with low-resource languages, even with the ones unseen during pretraining, and that the script is a critical component in this adaptation. NLP technologies are becoming increasingly critical to accessing knowledge, connecting with our friends, and extracting meaningful information from large quantities of text. In this thesis, we present concrete and usable solutions to ensure that we can build accurate NLP systems for the most significant number of domains and languages at a reasonable cost. For those who cannot make it in person, a video-conference link will be shared in the following google doc: https://docs.google.com/document/d/1YW1sa_x6oTLiXzgXoc2vcJqxaiZmhyu4TUGgl_D… Best, Benjamin Muller

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2025

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Corpora