- Corpora - ELRA lists

[Corpora-List]Two postdoc positions in Transfer Learning for Demographic Factors from September 2022
by mail＠dirkhovy.com 20 Jun '22

20 Jun '22

2-year Postdoc position in Natural Language Processing on Incorporating Demographic Factors into Natural Language Processing Models Funded by ERC Starting grant INTEGRATOR <https://milanlproc.github.io/project/integrator/> Start: from September 2022 Dirk Hovy, Bocconi University and MilanLP group Posting: https://bit.ly/3tk5UR6 <https://bit.ly/3tk5UR6> Application Form: https://bit.ly/3Q5j7qv <https://bit.ly/3Q5j7qv> Project: The goal of the INTEGRATOR project is to develop novel data sets, theories, and algorithms to incorporate demographic factors into language technology. This will improve performance of existing tools for all users, reduce demographic bias, and enable completely new applications. Language reflects demographic factors like our age, gender, etc. People actively use this information to make inferences, but current language technology (NLP) fails to account for demographics, both in language understanding (e.g., sentiment analysis) and generation (e.g., chatbots). This failure prevents us from reaching human-like performance, limits possible future applications, and introduces systematic bias against underrepresented demographic groups. Solving demographic bias is one of the greatest challenges for current language technology. Failing to do so will limit the field and harm public trust in it. Bias in AI systems recently emerged as a severe problem for privacy, fairness, and ethics of AI. It is especially prevalent in language technology, due to language's rich demographic information. Since NLP is ubiquitous (translation, search, personal assistants, etc.), demographically biased models creates uneven access to vital technology. Despite increased interest in demographics in NLP, there are no concerted efforts to integrate it: no theory, data sets, or algorithmic solutions. INTEGRATOR will address these by identifying which demographic factors affect NLP systems, devising a bias taxonomy and metrics, and creating new data. These will enable us to use transfer and reinforcement learning methods to build demographically aware input representations and systems that incorporate demographics to improve performance and reduce bias. Demographically aware NLP will lead to high-performing, fair systems for text analysis and generation. This ground-breaking research advances our understanding of NLP, algorithmic fairness, and bias in AI, and creates new research resources and avenues. Successful candidates will work actively on novel directions in NLP, machine learning, and neural networks for representation learning, and transfer learning in various languages, and collaborate closely with Prof. Hovy as well as the lab. The candidates will innovate in both NLP and social sciences. Successful candidates will have to prove * excellent programming skills in Python (additional languages like C++, R, Julia are a plus), * knowledge of current neural network models for transfer and few-shot learning and * implementation tools for neural networks (e.g. PyTorch, Tensorflow, etc.) * prove strong track record in top-tier venues in the field of NLP/ Machine Learning. * fluency in spoken and written English. Knowledge of Italian is NOT a requirement. INFORMATION * Application deadline: July 7 2022 * Skype interviews will take place during July 2022 * Starting date: from September 2022, or any time thereafter * Duration: 2 years, 1 year extension possible * Salary: 42k EUR gross per annum (median salary in Milan is 37k EUR). Applicants from outside Italy may qualify for a researcher taxation scheme with reduced tax load. HOW TO APPLY The official application must be sent via https://bit.ly/3Q5j7qv <https://bit.ly/3Q5j7qv> Informal enquiries can be sent by email to Dirk Hovy (dirk.hovy(a)unibocconi.it <mailto:dirk.hovy@unibocconi.it>). You can find more information about the call here: https://bit.ly/3tk5UR6 <https://bit.ly/3tk5UR6>

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Fully-funded PhD position “Computer Science: Computational Linguistics & Corpus Annotation” (m/f/d), TIB – Leibniz Information Centre for Science and Technology, Germany
by Jennifer D'Souza 20 Jun '22

20 Jun '22

**Deadline fast-approaching** Dear colleagues and friends, The Data Science and Digital Libraries <https://www.tib.eu/en/research-development/research-groups-and-labs/data-sc…> at the TIB – Leibniz Information Centre for Science and Technology and University Library <https://www.tib.eu/en/> invites applications for a Research Associate/PhD Candidate with the following specializations: Natural Language Processing; Computational Linguistics; Corpus Annotation. *Description: * The PhD topics will be in the context of the Open Research Knowledge Graph ( https://www.orkg.org) and the project “SCINEXT - Neural-Symbolic Scholarly Innovation Extraction”, funded by the Federal Ministry of Education and Research (BMBF). The aim of these projects is to research and develop techniques for crowdsourcing, representing and managing semantically structured, rich representations of scholarly contributions and research data in knowledge graphs and thus develop a novel model for scholarly communication. In the context of the PhD thesis you will be responsible for conducting independent and original scientific research involving corpus development and annotation in organizing research contributions in the ORKG in a structured, semantic way, so other researchers can get a quick overview on the state-of-the-art in the field. You will participate in local, national and international collaboration activities. Given the multidisciplinary nature of the programme, we encourage applicants with a strong curiosity and interest in Science to apply. The tasks will focus on - Collaborating with researchers from different disciplines to gain familiarity with research problems and their contribution descriptions expressed in scholarly literature. - Conceptually designing, modelling and implementing ontology-based knowledge representations for crowdsourcing of the Open Research Knowledge Graph. - Annotation and curation of multidisciplinary scholarly contribution descriptions. *Application Deadline:** June 28th 2022* *Please apply online here:* https://www.tib.eu/en/tib/careers-and-apprenticeships/vacancies/details/ste… *Contact Information: *Dr. Jennifer D'Souza *Email:* jennifer.dsouza(a)tib.eu Best regards, Jennifer

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[Corpora-List]Call for Participation: Shared Task on Indian Language Summarization (ILSUM 2022)
by Parth Mehta 20 Jun '22

20 Jun '22

Apologies for the multiple postings. ---- *Indian Language Summarization (ILSUM 2022)* Website: https://ilsum.github.io/ To be organized in conjunction with FIRE 2022 (fire.irsi.res.in) 9th-13th December 2022 (Hybrid Event, hosted in Kolkata) Registration Deadline*: 22nd July 2022* ------------------------------------------------------- The first shared task on Indian Language Summarization (ILSUM) aims at creating an evaluation benchmark dataset for Indian Languages. While large-scale datasets exist for a number of languages like English, Chinese, French, German, Spanish, etc. no such datasets exist for any Indian languages. Through this shared task, we aim to bridge the existing gap. In the first edition, we cover two major Indian languages Hindi and Gujarati alongside Indian English, a widely recognized dialect of the English Language. It is a classic summarization task, where we will provide ~10,000 article-summary pairs for each language and the participants are expected to generate a fixed-length summary. *Timeline* ------------- 8th June - Task announced and Registrations open 22nd June - Training Data Release 1st August - Test Data Release 8th August - Run Submission Deadline 15th August - Results Declared 15th September - Working notes due 9th-13th December - FIRE 2022 (Hybrid Event hosted at Kolkata) *Organisers* ---------------- Bhavan Modha, University of Texas at Dallas, USA Shrey Satapara, Indian Institute of Technology, Hyderabad, India Sandip Modha, LDRP-ITR, Gandhinagar, India Parth Mehta, Parmonic, USA *For regular updates subscribe to our mailing list: **ilsum(a)googlegroups.com <+ilsum(a)googlegroups.com>* Regards, Parth Mehta Co-organiser, ILSUM 2022

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[Corpora-List]automatic stance detection
by Florentina Hristea 20 Jun '22

20 Jun '22

Dear all, On behalf of “Frontiers”, the third most cited publisher, I’m happy to let you know that a new research topic has been launched and will be supervised by Cornelia Caragea and myself: automatic stance detection. Contributions to “Frontiers in Artificial Intelligence” and/or “Frontiers in Big Data” concerning this hot topic are invited. We are collaborating primarily with “Frontiers in Artificial Intelligence”, but both types of submissions are possible – as you will see in the research topic’s presentation page. Stance detection in natural language texts deals with determining the position (or stance) of a text producer towards a target or a set of targets. This Research Topic specifically addresses all aspects related to stance detection and its applications, both from a theoretical and practical viewpoint. We are looking for contributions in the form of Review, Original Research, Brief Research Report, Perspective, Technology and code etc. submission articles on substantial, original, and unpublished research in the following areas, including, but not limited to: • sentiment analysis in stance detection • perspective identification in stance detection • sarcasm/irony detection in stance detection • controversy detection in stance detection • argument mining in stance detection • biased language detection in stance detection • novel algorithms for stance detection: feature-based machine learning approaches, deep learning approaches, and ensemble learning approaches • novel datasets for stance detection You can check this research topic’s detailed presentation, submission deadlines and instructions for authors at: https://www.frontiersin.org/research-topics/40998/automatic-stance-detection Please note that submitting papers is possible even in the absence of a previously submitted abstract (although we would appreciate knowing what to expect in advance). Submission deadline can be extended by one month (but no longer) upon request. For any questions regarding the topic itself, submission etc., please don’t hesitate to contact me (fhristea(a)fmi.unibuc.ro<mailto:fhristea@fmi.unibuc.ro>). Looking forward to receiving your contributions, Florentina Hristea https://cs.unibuc.ro/~fhristea/

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[Corpora-List]CoCo4MT 2nd CFP - The First Workshop on Corpus Generation and Corpus Augmentation for Machine Translation
by Shabnam Tafreshi 19 Jun '22

19 Jun '22

-- Apologies for cross posting -- The First Workshop on Corpus Generation and Corpus Augmentation for Machine Translation (CoCo4MT)https://sites.google.com/view/coco4mt @ AMTA – 2022 This 15th biennial conference of the Association for Machine Translation in the Americas 12-16 September 2022, Orlando, Florida, USA INVITED TALKS Julia Kreutzer Google Research More TBA... SCOPE It is a well-known fact that machine translation systems, especially those that use deep learning, require massive amounts of data. Several resources for languages are not available in their human-created format. Some of the types of resources available are monolingual, multilingual, translation memories, and lexicons. Those types of resources are generally created for formal purposes such as parliamentary collections when parallel and more informal situations when monolingual. The quality and abundance of resources including corpora used for formal reasons is generally higher than those used for informal purposes. Additionally, corpora for low-resource languages, languages with less digital resources available, tends to be less abundant and of lower quality. CoCo4MT sets out to be the first workshop centered around research that focuses on corpora creation, cleansing, and augmentation techniques specifically for machine translation. We accept work that covers any spoken language (including high-resource languages) but we are specifically interested in those submissions that are on languages with limited existing resources (low-resource languages) where resources are not highly available. The goal of this workshop is to begin to close the gap between corpora available for low-resource translation systems and promote high-quality data for online systems that can be used by native speakers of low-resource languages is of particular interest. Therefore, It will be beneficial if the techniques presented in research papers include their impact on the quality of MT output and how they can be used in the real world. CoCo4MT aims to encourage research on new and undiscovered techniques. We hope that submissions will provide high-quality corpora that is available publicly for download and can be used to increase machine translation performance thus encouraging new dataset creation for multiple languages that will, in turn, provide a general workshop to consult for corpora needs in the future. The workshop’s success will be measured by the following key performance indicators: - Promotes the ongoing increase in quality of machine translation systems when measured by standard measurements, - Provides a meeting place for collaboration from several research areas to increase the availability of commonly used corpora and new corpora, - Drives innovation to address the need for higher quality and abundance of low-resource language data. TOPICS We are highly interested in original research papers on the topics below; however, we welcome all novel ideas that cover research on corpora techniques. - Difficulties with using existing corpora (e.g., political considerations or domain limitations) and their effects on final MT systems, - Strategies for collecting new MT datasets (e.g., via crowdsourcing), - Data augmentation techniques, - Data cleansing and denoising techniques, - Quality control strategies for MT data, - Exploration of datasets for pretraining or auxiliary tasks for training MT systems. SUBMISSION INFORMATION There is one type of submission in the workshop: Research, review and position paper. The length of each paper should be at least four (4) and not exceed ten (10) pages, plus unlimited pages for references. Submissions should be formatted according to the official AMTA 2022 style templates (PDF, LaTeX, Word). Accepted papers will be published on-line in the AMTA 2022 proceedings which includes the ACL Anthology and will be presented at the conference either orally or as a poster. Submissions must be anonymized and should be done using the official conference management system (https://cmt3.research.microsoft.com/AMTA2022). Scientific papers that have been or will be submitted to other venues must be declared as such, and must be withdrawn from the other venues if accepted and published at CoCo4MT. The review will be double-blind. We would like to encourage authors to cite papers written in ANY language that are related to the topics, as long as both original bibliographic items and their corresponding English translations are provided. Registration will be handled by the main conference. (To be announced) IMPORTANT DATES June 1, 2022 – Call for papers released June 15, 2022 – Second call for papers June 29, 2022 – Third and final call for papers July 13, 2022 – Paper submissions due July 27, 2022 – Notification of acceptance August 7, 2022 – Camera-ready due August 31, 2022 – Video recordings due September 16, 2022 - CoCo4MT workshop CONTACT CoCo4MT Workshop Organizerscoco4mt2022(a)googlegroups.com ORGANIZING COMMITTEE (listed alphabetically) Constantine Lignos Brandeis University John E. Ortega New York University and University of Santiago de Compostela (CITIUS) Katharina Kann University of Colorado Boulder Maja Popopvić ADAPT Centre at Dublin City University Marine Carpuat University of Maryland Shabnam Tafreshi University of Maryland William Chen Carnegie Mellon University PROGRAM COMMITTEE (listed alphabetically tentative) Abteen Ebrahimi University of Colorado Boulder Adelani David Saarland University Ananya Ganesh University of Colorado Boulder Alberto Poncelas ADAPT Centre at Dublin City University Amirhossein Tebbifakhr University of Trento Anna Currey Amazon Arturo Oncevay University of Edinburgh Atul Kr. Ojha National University of Ireland Galway Bharathi Raja Chakravarthi National University of Ireland Galway Beatrice Savoldi University of Trento Bogdan Babych Heidelberg University Briakou Eleftheria University of Maryland Dossou Bonaventure Mila Quebec AI Institute Duygu Ataman New York University Eleni Metheniti Université Toulosse - Paul Sabatier Francis Tyers Indiana University Jasper Kyle Catapang University of Birmingham John E. Ortega New York University and USC - CITIUS José Ramom Pichel Campos Universidade de Santiago de Compostela - CITIUS Kalika Bali Microsoft Koel Dutta Chowdhury Saarland University Liangyou Li Huawei Manuel Mager University of Stuttgart Maria Art Antonette Clariño University of the Philippines Los Baños Mathias Müller University of Zurich Nathaniel Oco De La Salle University Niu Xing Amazon Pablo Gamallo Universidade de Santiago de Compostela - CITIUS Rico Sennrich University of Zurich Sangjee Dondrub Qinghai Normal University Santanu Pal Saarland University Sardana Ivanova University of Helsinki Shantipriya Parida Silo AI Surafel Melaku Lakew Amazon Tommi A Pirinen University of Tromsø Valentin Malykh Moscow Institute of Physics and Technology Xu Weijia University of Maryland -- *Shabnam Tafreshi, PhD* *Assistant Research Scientist* *Computational Linguistics, NLP* *UMD: ARLIS @ College Park* *"All the problems of the world could be settled easily, if people only willing to think."* *-Thomas J. Watson*

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[Corpora-List][CfP] LaCATODA 2022 at ACII 2022, Nara, Japan (Linguistic and Cognitive Approaches to Dialog Agents)
by Ptaszynski Michal 19 Jun '22

19 Jun '22

Dear Colleagues, ** Sorry for cross-postings ** This year our workshop LaCATODA 2022 will be co-located with ACII 2022. Please, consider submitting a paper. The accepted papers will be published in the ACII workshop proceedings indexed by IEEExplore. Best regards, Michal Ptaszynski in the name of LaCATODA 2022 organizers, Michal PTASZYNSKI, Ph.D., Associate Professor Department of Computer Science Kitami Institute of Technology, 165 Koen-cho, Kitami, 090-8507, Japan TEL/FAX: +81-157-26-9327 michal(a)mail.kitami-it.ac.jp http://arakilab.media.eng.hokudai.ac.jp/~ptaszynski/ ========================================================== The Eighth Linguistic and Cognitive Approaches to Dialog Agents (LaCATODA 2022) (ACII 2022 Workshop) http://arakilab.media.eng.hokudai.ac.jp/ACII2022/ Venue: Nara, Japan & online (in conjunction with ACII, https://acii-conf.net/2022/) ========================================================== WHAT IS LaCATODA? A multidisciplinary workshop for researchers who develop dialog agents and methods for achieving more natural machine-generated conversation or study problems of human communication which are difficult to mimic algorithmically. We are interested in original papers on systems and ideas for systems that use common sense knowledge and reasoning, affective computing, cognitive methods, learning from broad sets of data and acquiring knowledge, or language and user preferences. ------------------------------------------------------------------ Important Dates: Paper submission: 20 July 2022 (11:59PM UTC-12:00, "anywhere on Earth") Notification of acceptance: 4 August 2022 Camera-Ready submission: 14 June 2022 LaCATODA 2022 Workshop: 17 October 2022 Submission: https://easychair.org/conferences/?conf=lacatoda2022 ------------------------------------------------------------------ Relevant Topics: - Affective computing - Agent-based information retrieval - Attention and focus in dialog processing - Artificial assistants - Artificial tutors - Common sense, knowledge and reasoning - Computational cognition - Conversational theories - Daily life dialog systems - Emotional intelligence simulations - Ethical reasoning - Humor processing - Language acquisition - Machine learning for / from dialogs - Text mining for / from dialogs - Philosophy of interaction / communication - Preference models - Unlimited question answering - User modeling - Wisdom of Crowds approaches - World knowledge acquisition - Systems and approaches combining above topics Organizers: Rafal Rzepka, Hokkaido University, Japan Jordi Vallverdú, Autonomous University of Barcelona, Spain Andre Wlodarczyk, Charles de Gaulle University, France Michal Ptaszynski, Kitami institute of Technology, Japan Pawel Dybala, Jagiellonian University, Poland

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[Corpora-List]Johns Hopkins University: Postdoc Positions
by Mark Dredze 17 Jun '22

17 Jun '22

The Center for Language and Speech Processing (CLSP) at Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record. Possible research topics include: - Explainable AI, natural language processing and medicine - Text generation and training large language models - Information extraction, retrieval, question answering, and human-in-the-loop learning Johns Hopkins University is a private university located in Baltimore, Maryland with easy access to a number of affordable and vibrant neighborhoods. CLSP is one of the world’s largest academic centers focused on speech and language with a dozen faculty members and over 80 graduate students. It has a history of placing students in top academic and industry positions. Applicants are not required to be US citizens or permanent residents. Details and application information: https://www.clsp.jhu.edu/employment-opportunities/

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[Corpora-List][CFP] 2nd Multilingual Representation Learning (MRL) Workshop at EMNLP 2022
by Gozde Gul 17 Jun '22

17 Jun '22

Dear all, It is our great pleasure to invite you to the second edition of multilingual representation learning that will be held at EMNLP 2022 (as a hybrid WS) on December 8, 2022. The details regarding the paper submission and the shared task are given below: ----------------------------- IMPORTANT DATES ----------------------------- *- Latest ARR deadline for paper submissions: September 1, 2022* - The last ARR commitment deadline: October 15, 2022 - Paper notifications: November 2, 2022 - Camera-Ready Papers due: November 9, 2022 - Main Conference: December 7-11, 2022 *- Workshop: December 8, 2022* (All deadlines are 11.59 pm UTC -12h (“anywhere on Earth”)) --------------------------- AIMS AND SCOPE --------------------------- The 2nd MRL Workshop invites participants to share and discuss recent findings on multi-lingual representation learning methods and their application in different settings. The main objectives of the workshop will be: To construct and present a wide array of multi-lingual representation learning methods, including their theoretical formulation and analysis, practical aspects such as the application of current state-of-the-art approaches in transfer learning to different tasks or studies on adaptation into previously under-studied context; To provide a better understanding on how the language typology may impact the applicability of these methods and motivate the development of novel methods that are more generic or competitive in different languages; To promote collaborations in developing novel software libraries or benchmarks in implementing or evaluating multi-lingual models that would accelerate progress in the field. By allowing a communication means for research groups working on machine learning, linguistic typology, or real-life applications of NLP tasks in various languages, to share and discuss their recent findings, our ultimate goal is to support rapid development of NLP methods and tools that are applicable to a wider range of languages. ---------------------- SUBMISSIONS ---------------------- Research papers: We invite all potential participants to submit their novel research contributions in the related fields as long papers following the EMNLP 2021 long paper format (anonymized with 8 pages excluding the references, and an additional page for the camera-ready versions for the accepted papers). All accepted research papers will be published as part of our workshop proceedings and presented either as oral or poster presentations. Our research paper track only accepts submissions made to the ACL Rolling Review. Extended abstracts: Besides long paper submissions, we also invite previously published or ongoing and incomplete research contributions to our non-archival extended abstract track. All extended abstracts can use the same EMNLP template with a 2-page limit, excluding the bibliography. Extended abstracts can be submitted to the workshop submission system using the softconf link: https://softconf.com/emnlp2022/mrl-2022 <https://urldefense.proofpoint.com/v2/url?u=https-3A__softconf.com_emnlp2022…> . ---------------------- Shared Task ---------------------- MRL 2022 features a new shared task on Multilingual Clause-level Morphology, which aims to provide a new evaluation benchmark for assessing multilingual representation learning models in terms of linguistic and cross-lingual generalization capabilities. We invite all interested peers in getting in touch about participation following the website https://sigtyp.github.io/st2022-mrl.html and mailing list participants-mcmsharedtask-2022(a)googlegroups.com. We anticipate awarding a prize for the shared task winning team and a presentation devoted to them. ------------------------- Best Paper Award ------------------------- A Best Paper Award will be presented at the workshop. ------------------------- Invited Speakers ------------------------- Ev Fedorenko, Massachusetts Institute of Technology Kyunghyun Cho, New York University Razvan Pascanu, DeepMind ------------------------ *Contact * Email: mrlw2022(a)gmail.com Website: https://sigtyp.github.io/ws2022-mrl.html *Organizers: * Duygu Ataman Orhan Firat Hila Gonen Jamshidbek Mirzakhalov Kelechi Ogueji Sebastian Ruder Gözde Gül Şahin On behalf of the organization committee, --------------------------- Gözde Gül Şahin Assistant Professor Computer Engineering Department Koç University https://gozdesahin.github.io/

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[Corpora-List]Webminar by Mikel Artetxe (FAIR (Meta AI))
by HiTZ zentroa 16 Jun '22

16 Jun '22

Dear colleague, The last post concerning the upcoming HiTZ webinar included incorrect information about the summary. This email contains the correct information. Apologies for the mix up! We are happy to announce an additional webinar in the Language Technology webinar series organized by the HiTZ research center (Basque Center for Language Technology, http://hitz.eus). Instead of the usual afternoon hour, it will take place at 10:00am CET (June 24). Next webinar: Speaker: Mikel Artetxe (FAIR (Meta AI)) Title: Is scale all you need? Date: Jun 24, 2022, 10:00 CET Summary: Every once in a while, a new language model with gazillion parameters makes a big splash in Twitter, smashing the previous SOTA in some benchmarks or showing some impressive emerging capabilities. While some may argue that scaling will eventually solve NLP, others are skeptical about the scientific value of this trend. In this talk, I will argue that scaling is not just engineering, but also comes with exciting research questions. I will present some of our recent work in the topic, and discuss our efforts to make large language models more accessible for the community. Bio:Mikel Artetxe is a Research Scientist at FAIR (Meta AI). His primary area of research is multilingual NLP. Mikel was one the pioneers of unsupervised machine translation, and has done extensive work on cross-lingual representation learning. More recently, he has also been working on natural language generation, few-shot learning, and large-scale language models. Prior to joining FAIR, Mikel did his PhD at the IXA group at the University of the Basque Country, and interned at DeepMind, FAIR and Google. Check past and upcoming webinars at the following url: http://www.hitz.eus/webinars If you are interested in participating, please complete this registration form: http://www.hitz.eus/webinar_izenematea If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info Best wishes, HiTZ Zentroa Unsuscribe: If you do not wish to receive further emails from us, please feel free to contact us

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[Corpora-List]Webminar by Mikel Artetxe (FAIR (Meta AI))
by HiTZ zentroa 16 Jun '22

16 Jun '22

*** We apologize for the multiple copies of this email. In case y Dear colleague, We are happy to announce an additional webinar in the Language Technology webinar series organized by the HiTZ research center (Basque Center for Language Technology, http://hitz.eus). Instead of the usual afternoon hour, it will take place at 10:00am CET (June 24). Next webinar: Speaker: Mikel Artetxe (FAIR (Meta AI)) Title: Is scale all you need? Date: Jun 24, 2022, 10:00 CET Summary: The development of advanced spoken language technologies based on automatic speech recognition (ASR) and text-to-speech synthesis (TTS) has enabled computers to either learn how to listen or speak. Many applications and services are now available but still support fewer than 100 languages. Nearly 7000 living languages that are spoken by 350 million people remain uncovered. This is because the construction is commonly done based on machine learning trained in a supervised fashion where a large amount of paired speech and corresponding transcription is required. In this talk, we will introduce a semi-supervised learning mechanism based on a machine speech chain framework. First, we describe the primary machine speech chain architecture that learns not only to listen or speak but also to listen while speaking. The framework enables ASR and TTS to teach each other given unpaired data. After that, we describe the use of machine speech chain for code-switching and cross-lingual ASR and TTS of several languages, including low-resourced ethnic languages. Finally, we describe the recent multimodal machine chain that mimics overall human communication to listen while speaking and visualizing. With the support of image captioning and production models, the framework enables ASR and TTS to improve their performance using an image-only dataset. Summary: Every once in a while, a new language model with gazillion parameters makes a big splash in Twitter, smashing the previous SOTA in some benchmarks or showing some impressive emerging capabilities. While some may argue that scaling will eventually solve NLP, others are skeptical about the scientific value of this trend. In this talk, I will argue that scaling is not just engineering, but also comes with exciting research questions. I will present some of our recent work in the topic, and discuss our efforts to make large language models more accessible for the community. Bio:Mikel Artetxe is a Research Scientist at FAIR (Meta AI). His primary area of research is multilingual NLP. Mikel was one the pioneers of unsupervised machine translation, and has done extensive work on cross-lingual representation learning. More recently, he has also been working on natural language generation, few-shot learning, and large-scale language models. Prior to joining FAIR, Mikel did his PhD at the IXA group at the University of the Basque Country, and interned at DeepMind, FAIR and Google. Check past and upcoming webinars at the following url: http://www.hitz.eus/webinars If you are interested in participating, please complete this registration form: http://www.hitz.eus/webinar_izenematea If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info Best wishes, HiTZ Zentroa Unsuscribe: If you do not wish to receive further emails from us, please feel free to contact us

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