- Corpora - ELRA lists

[Job] Postdoctoral fellow: Georgetown University Neuroscience of Language training program (Washington, DC)
by Nathan Schneider 21 Jul '22

21 Jul '22

Sharing on behalf of colleagues—note that applicants may come from a variety of fields! See contact info at the bottom of the ad. Postdoctoral fellow: Georgetown University Neuroscience of Language training program (Washington, DC) Georgetown University’s new Neuroscience of Language T32 training program <https://sites.google.com/georgetown.edu/neuro-lang> is seeking postdoctoral fellows. The Neuroscience of Language program provides training in the brain basis of language, as well as sensory, motor, and cognitive systems as they pertain to language and communication. Georgetown has a number of faculty focused on Neuroscience of Language research, ranging from basic work on auditory or language processing (spoken, signed, and written language) to clinical trials in adults and children with brain injuries affecting language. Interactions with Georgetown’s highly regarded Linguistics Department, as well as Children’s National Hospital and MedStar National Rehabilitation Hospital, provide us with access to additional faculty and research populations and further enrich the training environment. Individuals with doctoral degrees from any field related to Neuroscience of Language (Neuroscience, Cognitive Science, Linguistics, Psychology, Communication Disorders, etc.) are encouraged to apply. Fellows will be supported for two years and will develop an individualized training plan to provide expertise across disciplines important to Neuroscience of Language research. Fellows will take coursework as needed and will participate in a regular journal club and seminar series, clinical experiences, community engagement activities, and professional development activities, in addition to conducting research in the neuroscience of language. The overall goal of the program is to develop well-rounded scientists who have a broad perspective on basic and clinical Neuroscience of Language. Fellows will work with one or more of the following investigators: Drs. Thomas Coate, Guinevere Eden, Rhonda Friedman, William Gaillard, Anna Greenwald, Xiong Jiang, Elissa Newport, Josef Rauschecker, Max Riesenhuber, Ella Striem-Amit, Ted Supalla, Peter Turkeltaub, and Michael Ullman. Collaborations among our faculty are common and a strength of our program. Appointments are funded at standard NIH NRSA stipend rates, with an initial one-year term to be renewed for an additional year if fellows meet the program requirements. U.S. citizens or permanent residents who currently hold a doctoral degree or will have met all doctoral program requirements before starting the program are eligible to apply. Individuals from groups recognized to be underrepresented in the sciences are encouraged to apply <http://www.nsf.gov/statistics/wmpd/>. Please submit the following application materials via the application form <https://forms.gle/eEBab9cYSGwYYmrk7>. - CV - Personal statement describing career goals, prior research, goals for postdoctoral training, and lab(s) of interest (3 pages) - Names and contact information for three references - Writing sample (manuscript or dissertation) Contact Dr. Peter Turkeltaub (peter.turkeltaub(a)georgetown.edu) with any questions about the program or eligibility. Contact Rachel Galginaitis ( rg1171(a)georgetown.edu) with questions about the application process. -- Nathan Schneider Assistant Professor of Linguistics and Computer Science, Georgetown University http://nathan.cl

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Shared Task on Dialect Identification
by Salam Khalifa 21 Jul '22

21 Jul '22

Hello All, We are pleased to announce the *Nuanced Arabic Dialect Identification (NADI)* shared task as part of the Workshop on Arabic NLP WANLP2022 <https://sites.google.com/view/wanlp2022/>. *Summary:* Arabic has a widely varying collection of dialects. Many of these dialects remain under-studied due to the rarity of resources. The goal of the Nuanced Arabic Dialect Identification (NADI) shared task series is to alleviate this bottleneck by providing datasets and modeling opportunities for participants to carry out dialect identification. Dialect identification is the task of automatically detecting the source variety of a given text or speech segment. In addition to nuanced dialect identification at the country level, NADI 2022 also offers a new subtask focused on country-level sentiment analysis. While we invite participation in either of the two subtasks, we hope that teams will submit systems to both tasks (i.e., participate in the two tasks rather than only one task). By offering two subtasks, we hope to receive systems that exploit diverse machine learning architectures. This could include multi-task learning systems as well as sequence-to-sequence architectures in a single model such as the text-to-text Transformer. Other approaches could also be possible. We introduce the two subtasks next. *Organizers:* Muhammad Abdul-Mageed, Chiyu Zhang, Abdelrahim Elmadany, Nizar Habash, and Houda Bouamor. To find more information about the shared task please visit: https://nadi.dlnlp.ai/ Looking forward to your participation, Salam Khalifa (On behalf of the WANLP publicity chairs) -- *Salam Khalifa* *PhD Student* *Linguistics Department* *Institute for Advanced Computational Science (IACS)* *Stony Brook University* salam.khalifa(a)stonybrook.edu

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CfP: Special Issue of RiCL on spoken corpora
by Robbie Love 21 Jul '22

21 Jul '22

Dear colleagues You may be interested to know that I am guest editing a special issue of the Research in Corpus Linguistics (RiCL) journal on "Innovations in the compilation and analysis of spoken corpora". The deadline for proposals is in October. Please find more information below. If this is of interest to you and you would like to discuss any ideas you may have, then please don't hesitate to email me directly. Best wishes Robbie *** Corpora derived from recordings of spoken language present unique challenges for linguists, from the perspectives of corpus design, compilation, processing and analysis, among others. Over the last few decades, there have been many developments in these areas, largely driven by technological innovations, for example: the ubiquity of digital recording devices for the easy capture of speech; the wide availability of video and audio data, from a variety of discourse contexts; advancements in automated transcription; developments in the exploitation of multimodal corpora; and advancements in the functionality of popular corpus tools to process highly-annotated corpora. This special issue of RiCL intends to capture recent innovations in the compilation and analysis of spoken corpora - both monomodal and multimodal - and highlight the current challenges and future opportunities in this area of study. Potential topics for the special issue include innovations in: * The design of (monomodal or multimodal) spoken corpora in a variety of domains * The collection, processing and exploitation of metadata (e.g. social variables, contextual variables, etc.) * The transcription of audio or audio-visual data * The analysis of spoken corpora, including but not limited to: theoretical frameworks, tool development, visualisation * The generation of knowledge about language and communication deriving from spoken corpora * The annotation and processing of spoken corpus data * The applications and impacts of spoken corpus analysis * The compilation and analysis of spoken corpora in lesser-studied language varieties This is an indicative and non-exhaustive list. To be clear, research on any language variet(y/ies) is welcome. If you have an idea but are not sure whether it would be suitable, please get in touch. Important Dates * Deadline for proposals: October 7, 2022 * Outcome of proposal review: October 28, 2022 * Deadline for manuscript first drafts: May 5, 2023 * Notification of reviewer outcome: September 1, 2023 * Deadline for manuscript final drafts: December 15, 2023 Special issue publication: Spring 2024 Proposal Format & Submission Submit a one-page abstract and tentative title for your proposed paper. The abstract should introduce the topic, motivate the study, summarise the methods and (where appropriate) describe the data to be analysed. Preliminary results are welcome but not required (i.e. we will consider proposals based on planned but not yet completed research). Please also include your name(s) and full contact information. Submit your proposal to Robbie Love (r.love(a)aston.ac.uk<mailto:r.love@aston.ac.uk>). RiCL's submission guidelines can be found at: https://ricl.aelinco.es/index.php/ricl/about/submissions Peer Review All accepted manuscripts will undergo double-blind peer review. Dr Robbie Love FHEA (he/him) Lecturer in English Language Director of Undergraduate English Programmes [cid:image001.png@01D89D20.AF468BA0] Department of English, Languages and Applied Linguistics, NW914A Birmingham, B4 7ET, UK aston.ac.uk @lovermob<https://twitter.com/lovermob>

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Large-scale Datasets for Persian Question Answering (University of Isfahan)
by mozafari.jamshid＠gmail.com 21 Jul '22

21 Jul '22

Dear colleagues, We are pleased to announce that the BigData Lab of the University of Isfahan has presented some large-scale datasets for Question Answering, Machine Reading Comprehension, and Answer Selection for the Persian language. We are very proud to share these datasets with our colleagues. These datasets are accessible from the links below: (1) PersianQuAD: The Native Question Answering Dataset for the Persian Language DOI: https://doi.org/10.1109/ACCESS.2022.3157289 Github: https://github.com/BigData-IsfahanUni/PersianQuAD Kaggle: https://www.kaggle.com/jamshidjdmy/persianquad (2) PerAnSel: A Novel Deep Neural Network-Based System for Persian Question Answering DOI: https://doi.org/10.1155/2022/3661286 Github: https://github.com/BigData-IsfahanUni/PerAnSel Kaggle: https://www.kaggle.com/jamshidjdmy/peransel (3) ParSQuAD: Persian Question Answering Dataset based on Machine Translation of SQuAD 2.0 DOI: https://dx.doi.org/10.22133/ijwr.2021.293313.1101 Github: https://github.com/BigData-IsfahanUni/ParSQuAD Kaggle: https://www.kaggle.com/neginabadani/parsquad

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PhD Position on Unified Foundation models for Speech-to-Speech Translation at FBK and Naver Labs Europe
by Matteo Negri 21 Jul '22

21 Jul '22

-- Apologies for cross-posting. -- Have you recently completed or expect very soon an MSc or equivalent degree in computer science, artificial intelligence, computational linguistics, engineering, or a related area? Are you interested in carrying out research on Speech-to-Speech Translation during the next few years? Are you excited to spend a part of your life in 2 pleasant alpine cities in France (Grenoble) and Italy (Trento)? WE ARE LOOKING FOR YOU!!! The Machine Translation <https://ict.fbk.eu/units/hlt-mt/> (MT) group at Fondazione Bruno Kessler (Trento, Italy) in conjunction with Naver Labs Europe <https://europe.naverlabs.com/> (Grenoble, France) are pleased to announce the availability of the following fully-funded Ph.D. position at the Doctorate Program in Industrial Innovation of the University of Trento and Fondazione Bruno Kessler <https://iid.unitn.it/>. TITLE: Unified Foundation models for Speech-to-Speech Translation DESCRIPTION: Current trends in Artificial Intelligence are characterized by the migration from “task-specific models” to the so-called “foundation models”. The former are usually trained on large datasets labelled for specific target applications. The latter, much more reusable and flexible, are trained on a variety of unlabeled data to perform different tasks with minimal fine-tuning. In recent years, the introduction of such models (e.g. BERT, GPT-3) has opened an unprecedented range of opportunities, with an explosion of AI applications fueled by the power of transfer learning across diverse data and tasks. In line with this trend, this PhD aims at investigating and training deep neural architectures to build large multimodal sequence-to-sequence models able to encode input speech and text in a common space, also being able to decode output text or speech from a common representation. Such a multimodal architecture, if then made multilingual, will become the future unified foundation model for building automatic speech recognition (ASR), text-to-speech synthesis (TTS), speech-to-text translation (S2T) and speech-to-speech translation (S2S) systems from a single backbone. REQUIRED SKILLS: The ideal candidate must have recently completed or expect by October 31st, 2022, an MSc or equivalent degree in computer science, artificial intelligence, computational linguistics, engineering, or a closely related area. In addition, the applicant should: - Have interest in Machine and Speech Translation - Have experience in deep learning and machine learning, in general - Have good programming skills in Python and experience in PyTorch - Enjoy working with real-world problems and large data sets - Have good knowledge of written and spoken English - Enjoy working in a closely collaborating international team Working Environment The doctoral student will be employed at the MT group at Fondazione Bruno Kessler and will work for an equivalent amount of time in two different labs (TBD): - The NLP team at Naver Labs Europe (Grenoble, France) - The Machine Translation (MT) group at Fondazione Bruno Kessler (Trento, Italy) NAVER LABS is the R&D subsidiary of NAVER, Korea’s leading internet company. FBK has trained many scientists nowadays employed in leading IT companies in the world. Both groups have a long tradition in research on machine and speech translation. Benefits Fondazione Bruno Kessler offers an attractive benefits package, including a flexible work week, full reimbursement for conferences and summer schools, a competitive scholarship, an excellent team of supervisors and mentors, help for housing search, full health insurance, the possibility of Italian courses, sporting facilities, and free canteen at lunch During the student’s research stays at Naver Labs Europe (Grenoble, France), accommodation and travel expenses from and to Trento will be fully covered. Further Information For preliminary interviews, and should you need further information about the position, please contact Matteo Negri (negri(a)fbk.eu), Laurent Besacier ( laurent.besacier(a)naverlabs.com) and Ioan Calapodescu ( ioan.calapodescu(a)naverlabs.com) COMPLETE DETAILS AVAILABLE AT: <https://iecs.unitn.it/education/admission/call-for-application> http://iid.unitn.it/education/admission/call-for-application <https://iid.unitn.it/education/admission/call-for-application> IMPORTANT DATES: The deadline for application: August 23, 2022 | 16:00 (CEST) Potential candidates are strongly invited to contact us in advance for preliminary interviews. Precedence for interviews will be given to short-listed candidates that will send us a complete CV via email ( negri(a)fbk.eu, laurent.besacier(a)naverlabs.com, ioan.calapodescu(a)naverlabs.com) by August 5, 2022. Best Regards, Matteo Negri -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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Bilingual parallel dataset EN/ES
by Komal Florio 21 Jul '22

21 Jul '22

Dear all, I am looking for a bilingual parallel dataset in EN/ES or relevant shared tasks that may involve such linguistic resources. I do not have specific requirements in terms of the domain (or at least not in this exploratory phase), but it is mandatory that the two datasets were developed following exactly the same rules and with the same timestamp. Thanks very much! K. -- Komal Florio, PhD UNED Research Group in Natural Language Processing and Information Retrieval AVISO LEGAL. Este mensaje puede contener información reservada y confidencial. Si usted no es el destinatario no está autorizado a copiar, reproducir o distribuir este mensaje ni su contenido. Si ha recibido este mensaje por error, le rogamos que lo notifique al remitente. Le informamos de que sus datos personales, que puedan constar en este mensaje, serán tratados en calidad de responsable de tratamiento por la UNIVERSIDAD NACIONAL DE EDUCACIÓN A DISTANCIA (UNED) c/ Bravo Murillo, 38, 28015-MADRID-, con la finalidad de mantener el contacto con usted. La base jurídica que legitima este tratamiento, será su consentimiento, el interés legítimo o la necesidad para gestionar una relación contractual o similar. En cualquier momento podrá ejercer sus derechos de acceso, rectificación, supresión, oposición, limitación al tratamiento o portabilidad de los datos, ante la UNED, Departamento de Política Jurídica de Seguridad de la Información<https://www.uned.es/dpj>, o a través de la Sede electrónica<https://sede.uned.es/> de la Universidad. Para más información visite nuestra Política de Privacidad<https://descargas.uned.es/publico/pdf/Politica_privacidad_UNED.pdf>.

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Training data for ASR and MT in Danish and Irish (Gaelic)
by Elisa Di Nuovo 21 Jul '22

21 Jul '22

Dear members, I’m looking for public data that can be used to train a tool that performs Automatic Speech Recognition and Machine Translation. The languages are Danish and Gaelic. Thank you for your help, Best regards, Elisa Di Nuovo Elisa Di Nuovo PhD student @ University of Turin elisa.dinuovo(a)unito.it

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Deadline extension! [2nd CfP] METRICS 2022: ASIS&T VIRTUAL WORKSHOP ON INFORMETRICS AND SCIENTOMETRICS RESEARCH
by Tirthankar Ghosal 21 Jul '22

21 Jul '22

Dear Colleagues, METRICS 2022 OC has decided to extend the deadline to submit your abstracts till August 5th. Looking forward to your submissions. Thank you. Best regards, Tirthankar METRICS 2022: ASIS&T VIRTUAL WORKSHOP ON INFORMETRICS AND SCIENTOMETRICS RESEARCH Virtual workshop sponsored by ASIS&T SIG/MET ASIS&T 2022 Annual Meeting - Part I: Saturday, October 8, 2022, 8:00 a.m. – 12:00 p.m. EDT - Part II: Sunday, October 9, 2022, 8:00 a.m. – 12:00 p.m. EDT Website: https://www.asist.org/2022/06/14/metrics-2022-asist-virtual-workshop-on-inf… *CALL FOR ABSTRACTS* The ASIS&T Special Interest Group for Metrics (SIG/MET) invites contributions to the METRICS 2022 workshop, which will be held prior to the 85th ASIS&T Annual Meeting. The workshop continues the successful SIG/MET workshop series held annually since 2011 by providing an opportunity to present and discuss research related to the measurement of knowledge production, dissemination, and use among experienced researchers, young academics, and practitioners. We invite abstracts describing empirical or theoretical work, related but not limited to: - Altmetrics - Bibliometric-enhanced information retrieval - Bibliometrics - Informetrics - Open access - Open science - Patent analysis - Quantitative science studies - Research evaluation - Scholarly communication - Science communication - Science of science - Scientometrics *SUBMISSIONS* The following four types of submission are accepted: - *Research presentations*, for completed or in-progress research. [Presentation] - *Posters* for work in early stages or best presented visually. [Poster] - *Tutorials* for practical information on a tool or method. [Tutorial] - *Panels* for discussions on a specific topic. [Panel] Please indicate the type of submission by naming the file in the following format: Metrics22_First Author's Last Name + First Name Initials_Submission Type (e.g., Metrics22_ChenPY_Presentation). All submissions should be in the form of a *two-page extended abstract* using APA style and formatted according to the AM22 Proposal Template Instructions <https://growthzonesitesprod.azureedge.net/wp-content/uploads/sites/946/Temp…>. Where appropriate, up to three figures/tables can be provided. Do not include any author names on the file you upload. The abstracts of accepted papers and posters, as well as the presentation slides, will be deposited on Zenodo <https://zenodo.org/> to enhance the visibility and retrievability of the presented research. Please submit your abstract as a PDF to https://easychair.org/conferences/?conf=metrics2022 *Submissions will be evaluated by at least two independent reviewers based on their relevance to the workshop and their methodological soundness (where applicable), and brief feedback will be given in narrative format.* *AWARDS* Thanks to the generous sponsorship from the International Center for the Study of Research (ICSR) <https://www.elsevier.com/icsr>, the workshop will present the *Best Student Paper Awards* and *Best Paper Award* this year to recognize the excellence of the presenting work (excluding *posters*). Up to three awardees will be selected for the Best Student Paper Awards. *To be considered for the best student paper, the first author of the paper entered into this contest must be a full-time student at the time of submission*, irrespective of ASIS&T or SIG/MET membership. Please also indicate Student on the name of the submitted file, e.g., Metrics22_ChenPY_Presentation_Student, even if the co-authors are non-students. One best paper will also be selected from all accepted papers regardless of their topic. However, to ensure fairness, a paper cannot be awarded both as best paper and best student paper at the same time. In other words, if a student paper is selected to be the best paper, it will not be considered for the best student paper awards. *The winners of both awards will be decided by a double-blind peer review process from the eligible accepted submissions.* The awards will be decided before the presentations take place, but the authors must present at the workshop to qualify. *We offer a cash prize of $500 for the Best Paper Award and $250 for the Best Student Paper Award.* *IMPORTANT DATES* - Submissions due: Friday, August 5th, 2022 EDT - Notifications: Friday, August 26th, 2022 EDT *REGISTRATION* In an effort to provide an open venue for communication and discussion on metrics-related research, we are offering free registration for ASIS&T members and discounted registration fees for non-members this year. *Rate* *Member/Regular* *Member/Student* *Non-member/Regular* *Non-member/Student* Early (by August 12) $0 $0 $25 $10 After August 12 $25 $25 $50 $35 More information on registration rates can be found at https://www.asist.org/am22/22registration/. *ORGANIZERS* - Pei-Ying Chen, Indiana University, Bloomington, Indiana, USA ( peiychen(a)iu.edu) - Isabelle Dorsch, Heinrich Heine University Düsseldorf, Düsseldorf, Germany (isabelle.dorsch.hhu.de) - Fei Shu, Hangzhou Dianzi University, Hangzhou, China; Université de Montréal, Montréal, Canada (fei.shu(a)mail.mcgill.ca) *SPONSORS* International Center for the Study of Research <https://www.elsevier.com/icsr> -- +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Tirthankar Ghosal Researcher at UFAL, Charles University, CZ https://member.acm.org/~tghosal +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

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GailBot usage: Jeffersonian annotations for CA
by Andrew Mitchell 21 Jul '22

21 Jul '22

Hi list A bit of a random and potentially off-list query, but has anybody any experience in using GailBot for Jeffersonian annotations and mark ups to facilitate CA on audio transcriptions? If so, please write to me off-list because I'd really appreciate any tips and tricks on how to use it. Cheers Andrew ----- Andrew Mitchell PhD, MSc, MBPsS Course Leader: Engineering Management (H1N171) Module Leader: Engineering Business Environment (ENGT5219) Web of Science Researcher ID: AAT-8116-2021 Agile PM Practitioner: 1000728878 Room QB1.15D , Institute of Energy & Sustainable Development (IESD) Faculty of Computing, Engineering & Media, De Montfort University Leicester LE1 9BH +44(0)116 257 7957 https://orcid.org/0000-0002-3946-4094

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Shared Task on Propaganda Detection
by Salam Khalifa 21 Jul '22

21 Jul '22

Hello All, We are pleased to announce the *Propaganda Detection in Arabic Social Media Text* shared task as part of the Workshop on Arabic NLP WANLP2022 <https://sites.google.com/view/wanlp2022/>. *Summary:* Propaganda is defined as an expression of opinion or action by individuals or groups deliberately designed to influence the opinions or actions of other individuals or groups with reference to predetermined ends. This is achieved by means of well-defined rhetorical and psychological devices. Currently, propaganda (or persuasion) techniques have been commonly used on social media to manipulate or mislead social media users. More detail on the techniques can be found here: https://propaganda.qcri.org/annotations/definitions.html. The goal of the shared task is to build models for identifying such techniques in Arabic social media text (specifically tweets). *Organizers:* Firoj Alam, Hamdy Mubarak, Wajdi Zaghouani, Preslav Nakov, and Giovanni Da San Martino. To find more information about the shared task please visit: https://sites.google.com/view/propaganda-detection-in-arabic Looking forward to your participation, Salam Khalifa (On behalf of the WANLP publicity chairs) -- *Salam Khalifa* *PhD Student* *Linguistics Department* *Institute for Advanced Computational Science (IACS)* *Stony Brook University* salam.khalifa(a)stonybrook.edu

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