- Corpora - ELRA lists

Birmingham Corpus Linguistics Summer School and Sinclair lecture 11 - 14 Sept 2023 (CCRSS23)
by Michaela Mahlberg 02 Jun '23

02 Jun '23

The 7th summer school hosted by the Centre for Corpus Research at the University of Birmingham will take place from 11th to 14th September 2023. https://www.birmingham.ac.uk/schools/edacs/departments/englishlanguage/even… Who is it for? The summer school is open to undergraduate, postgraduate, and doctoral students, as well as researchers who want to improve their skills to apply corpus methods in their own research. Our summer school aims to equip participants with critical expertise in both the theory and practice of corpus-supported linguistic research. Building on the strengths of our Centre for Corpus Research (CCR)<https://www.birmingham.ac.uk/research/activity/corpus/index.aspx> and our guest speakers, we strive to offer participants a learning experience that benefits their own specific research needs and enriches their experience as researchers more widely. There will be the opportunity for participants to present their own work and receive feedback from our expert team. Given the specialised nature of the programme, a basic understanding of corpus linguistics is highly recommended. What’s the format? The summer school will be online and consist of synchronous and asynchronous elements. Prior to the synchronous part, participants will be expected to complete asynchronous activities consisting of self-study video lectures and hands-on materials. The synchronous part will take place from 11 to 14 September, 2023. Over the course of four days, participants will be actively involved in two kinds of sessions. First, hands-on sessions will put the emphasis on the learning of practical skills for the purpose of extracting and analysing corpus data of various kinds, and the application of this knowledge to specific research projects. Second, participants will learn about current corpus research and theoretical foundations from our team. What is it about? Topics typically covered in the programme include (non-exhaustive list and subject to change): Corpus linguistics for media analysis Analysis of spoken corpora CQPweb Introduction to R and tidyverse Web scraping with R Digital humanities and the study of fiction Sign language corpora Regular expressions Corpora and legal research Critical issues in keyness analysis Behavioral Profiles Machine learning in corpus linguistics Corpus-based discourse analysis Corpus linguistics and language learning Who are the teachers? Our local team of corpus linguists includes Dagmar Divjak<https://www.birmingham.ac.uk/staff/profiles/languages/divjak-dagmar.aspx>, Natalie Finlayson<https://www.birmingham.ac.uk/schools/edacs/departments/englishlanguage/staf…>, Jason Grafmiller<https://www.birmingham.ac.uk/schools/edacs/departments/englishlanguage/staf…>, Jack Grieve<https://www.birmingham.ac.uk/staff/profiles/elal/grieve-jack.aspx>, Michaela Mahlberg<https://www.birmingham.ac.uk/staff/profiles/elal/mahlberg-michaela.aspx>, Karen McAuliffe<https://www.birmingham.ac.uk/staff/profiles/law/mcauliffe-karen.aspx>, Petar Milin<https://www.birmingham.ac.uk/staff/profiles/languages/milin-petar.aspx>, Akira Murakami<https://www.birmingham.ac.uk/staff/profiles/elal/murakami-akira.aspx>, Florent Perek<https://www.birmingham.ac.uk/staff/profiles/elal/perek-florent.aspx>, Laurence Romain<https://www.birmingham.ac.uk/staff/profiles/languages/romain-laurence.aspx>, Adam Schembri<https://www.birmingham.ac.uk/staff/profiles/elal/schembri-adam.aspx>, Paul Thompson<https://www.birmingham.ac.uk/staff/profiles/elal/thompson-paul.aspx>, and Bodo Winter<https://www.birmingham.ac.uk/staff/profiles/elal/winter-bodo.aspx>. Guest speakers will include Robbie Love<https://robbielove.org/> (Aston University), Stephanie Evert<http://www.stephanie-evert.de/> (FAU Erlangen), Alexander Piperski<https://www.linguistik.phil.fau.de/person/alexander-piperski/> (FAU Erlangen) Sinclair lecture As every year, the annual Sinclair Lecture will take place during the Summer School. This year, the Lecture will be delivered on Monday 11 September by our very own Susan Hunston<https://www.birmingham.ac.uk/staff/profiles/elal/hunston-susan.aspx>. The Sinclair lecture will be an in-person event. Registration will open shortly via our webpage https://www.birmingham.ac.uk/schools/edacs/departments/englishlanguage/even… For updates also follow @CCR_UoB See you there!

1 0

Call for Book Chapter Submissions: "Empowering Low-Resource Languages With NLP Solutions"
by Pankaj Dadure 02 Jun '23

02 Jun '23

Dear Sir/Ma'am, I hope you are doing well and in good health. We are excited to announce a call for a book chapter for an upcoming book titled "*Empowering Low-Resource Languages With NLP Solutions.*" Link: https://www.igi-global.com/publish/call-for-papers/call-details/6596 The objective of this book is to provide an in-depth understanding of Natural Language Processing (NLP) techniques and applications specifically tailored for low-resource languages. We believe that your valuable insights and research in this domain would greatly enrich the content of this book. To ensure a comprehensive and high-quality book, all submitted chapters will undergo a rigorous peer-review process. The accepted book will be *indexed in Scopus and Web of Science*, thereby enhancing the visibility and impact of your work. The book aims to cover a wide range of topics related to NLP in low-resource languages. Some of the suggested topics, although not limited to, include: · Introduction to Low-Resource Languages in NLP · Language Resource Acquisition for Low-Resource Languages · Morphological Analysis and Morpho-Syntactic Processing · Named Entity Recognition and Entity Linking for Low-Resource Languages · Part-of-Speech Tagging and Syntactic Parsing · Machine Translation for Low-Resource Languages · Sentiment Analysis and Opinion Mining for Low-Resource Languages · Speech and Audio Processing for Low-Resource Languages · Text Summarization and Information Retrieval for Low-Resource Languages · Multimodal NLP for Low-Resource Languages · Code-switching and Language Identification for Low-Resource Languages · Evaluation and Benchmarking for NLP in Low-Resource Languages · Applications of NLP in Low-Resource Language Settings · Future Directions and Challenges in NLP We encourage you to contribute a book chapter focusing on any of the above-mentioned topics or related areas within the scope of NLP in low-resource languages. The submission guidelines are as follows: 1. Please submit a chapter proposal (maximum 500 words) outlining the objective, methodology, and expected outcomes of your proposed chapter by July 3, 2023, to the submission portal: https://www.igi-global.com/publish/call-for-papers/call-details/6596 2. Chapter proposals should include the title of the chapter, author(s) name and their affiliations. 3. All submissions should be original and should not have been previously published or currently under review elsewhere. 4. The chapters should be written in English and adhere to the formatting guidelines provided after the acceptance of the proposal. *Important Dates:* July 3, 2023: Proposal Submission Deadline July 17, 2023: Notification of Acceptance September 17, 2023: Full Chapter Submission October 31, 2023: Review Results Returned December 12, 2023: Final Acceptance Notification December 26, 2023: Final Chapter Submission Thank you for considering this invitation, and we look forward to receiving your valuable contribution to this book. If you have any further questions or require additional information, please do not hesitate to contact us. Best regards, Editorial Team Dr. Partha Pakray National Institute of Technology Silchar Email: partha(a)cse.nits.ac.in Dr. Pankaj Dadure University of Petroleum and Energy Studies Dehradun Email: pankajk.dadure(a)ddn.upes.ac.in Prof. Sivaji Bandyopadhyay Jadavpur University, Kolkata Email: sivaji.cse.ju(a)gmail.com

1 0

RANLP 2023 Student Workshop - Second Call for Papers
by Ivelina Nikolova 01 Jun '23

01 Jun '23

-----------------Apologies for cross-posting------------------- Second Call for Papers RANLP 2023 Student Research Workshop 4-6 September 2023 Varna, Bulgaria https://sites.google.com/view/ranlp-stud-2023/ The International Conference RANLP 2023 (http://ranlp.org/) would like to invite students at all levels (undergraduate, Master-, and PhD-students) to present their ongoing or completed work at the Student Research Workshop (https://sites.google.com/view/ranlp-stud-2023/). SUBMISSIONS We invite two types of student submissions: Full Papers must describe original unpublished work of the student in any topic area of the workshop. Full papers are limited to 8 pages for content, with 2 additional pages for references. Short Papers may describe either work in progress or a research proposal. They may also be in the style of a position paper that surveys and criticizes existing literature. Short papers must include clear directions for future research. Submissions of this type are limited to 6 pages for content, with 2 additional pages for references. All papers must be submitted in .pdf format through the START system (https://softconf.com/ranlp23/ranlp20t23stud/) . The papers should follow the format of the main conference, described at the RANLP website (http://ranlp.org/), Submissions page. All papers must have only student authors. Submissions with non-student authors will not be considered for review. After eventual acceptance of the paper, the authors could add their supervisor(s) in the Acknowledgments Section. The submissions must specify the student’s level (Bachelor-, Master-, or PhD) and the type of submission (Full or Short). Double submission Authors may submit the same paper at several conferences. In this case, they must notify the organizers by filling in the corresponding information in the submission form, as well as notifying the contact organizer by email. TOPICS OF INTEREST The aim of this workshop is to facilitate the exchange of knowledge between young researchers by providing an excellent opportunity to present and discuss their work and to receive mentorship and valuable feedback from an international research community. The research to be presented can come from any topic within Natural Language Processing (NLP) and Computational Linguistics, including but not limited to the following: Computational Social Science and Social Media; Computer-aided Language Learning; Dialogue and Interactive Systems; Discourse and Pragmatics; Ethics and NLP; Information Extraction; Information Retrieval and Text Mining; Intent Recognition and Detection; Interpretability and Analysis of Models for NLP; Language and Vision; Language Generation; Language Resources and Corpora; Linguistic Theories; Machine Translation and Computer-aided Translation Tools; Multilingual NLP; Multimodal Systems; NLP Applications – Biomedical, Educational, Healthcare, Financial, Legal, Semantic Web, etc.; Opinion Mining and Sentiment Analysis; Phonetics, Phonology, and Morphology; Question Answering; Semantics; Stylistic Analysis; Sublanguages and Controlled languages; Syntax: Tagging, Chunking, and Parsing; Temporal Processing; Text Categorization; Text Simplification and Readability Estimation; Text Summarisation; Text-to-Speech Synthesis and Speech Recognition; Textual Entailment. All accepted papers will be presented at the Student Workshop sessions (oral or poster) during the main conference days: 4-6 September 2023. The articles will be issued in a special Student Session proceedings and uploaded to the ACL Anthology. IMPORTANT DATES Submission deadline: 3 July 2023 Acceptance notification: 4 August 2023 Camera-ready deadline: 20 August 2023 Workshop: 4 - 6 September 2023 All deadlines are 11:59PM UTC-12:00 ("anywhere on Earth") ORGANISERS Momchil Hardalov (AWS AI Labs, Spain) Zara Kancheva (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Bulgaria) Boris Velichkov (Faculty of Mathematics and Informatics at Sofia University “St. Kliment Ohridski”, Bulgaria) Ivelina Nikolova-Koleva (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, and Sirma AI, Bulgaria) Milena Slavcheva (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Bulgaria)

1 0

PhD Studentship in IR/NLP/AI: Large Language Models for Academic SEarch and Recommendation
by Ingo Frommholz 01 Jun '23

01 Jun '23

Faculty of Science and Engineering Dean Research PhD Studentship LASER - Large Language Models for Academic SEarch and Recommendation Deadline: June 19, 2023 University of Wolverhampton, UK Applications are invited for doctoral study in Computer Science, Information Retrieval and Natural Language Processing on the topic of Large Language Models for Academic Search and Recommendation. Project Description Scientific publications are an important vehicle for understanding the world around us; they contain scientific evidence that informs researchers and decision-makers, with a high impact on society. However, the rapid and large number of publications, in particular on preprint servers, causes an information overload for everybody struggling to keep up with developments in their field. This makes finding relevant information of high quality a challenging task, which requires advanced scholarly search and recommendation solutions. Recent developments in Large Language Models (LLMs) are having a huge impact on Artificial Intelligence (AI) and related fields. LLMs are a type of AI trained on huge amounts of text, with ChatGPT/GPT-4 and Bard as popular examples. LLMs combined with conversational AI provide exciting new possibilities for interactive search and recommendation, but they are also suffering from severe flaws. While there are efforts to combine LLMs with, e.g., neural search, the endeavour of utilising LLMs to tackle information overload in academia has only started and more research is needed. This PhD studentship will explore how LLMs can be used to improve academic search and recommendation and what their benefits and limitations are. This may include integrating LLMs into search and recommendation services or utilising search to keep LLMs from "hallucinating". A further part of this project is to estimate the quality of publications. The PhD project provides exciting opportunities for the successful candidate to work with and critically reflect on innovative technologies at the forefront of AI that will shape our digital future. As a further incentive, the PhD candidate will be able to participate in an EU Horizon Europe Staff Exchange project, providing the opportunity to go on fully funded secondments to collaborate with an international network of researchers and industry partners. For further information regarding the project or an informal discussion please contact Director of Studies, Dr Ingo Frommholz <i.frommholz(a)wlv.ac.uk>. To apply for one of the above PhD Research Studentship applicants must hold a first class/distinction at Master and/or Bachelor level of study. Applications to include one identified project, a full CV (including 2 referee names and contact details), transcripts and a letter of application outlining the motivation for applying (maximum of 2 pages). Applicants from outside UK must provide evidence of English Language requirement as stated in https://www.wlv.ac.uk/research/research-degrees/ Application submission deadline is 10:00am BST 19 June 2023 to FSEPGR(a)wlv.ac.uk A shortlist of candidates will be prepared from the pool of applicants, in line with Faculty of Science and Engineering Post Graduate Research (PGR) studentship selection criteria, who will be invited to attend an interview with a panel of academic staff, week commencing 26 June 2023. Following this process, all successful candidates will be notified to enrol in July 2023 on a PhD degree programme. The studentship award will include tuition fees at home level for the first three years of full-time study including any write-up period fees and research support fees. For further information on fees https://www.wlv.ac.uk/apply/funding-costs-fees-and-support/fees-and-costs/r… Informal enquiries are welcome and should be directed to the individual Director of Studies mentioned above. Further information: https://www.wlv.ac.uk/schools-and-institutes/faculty-of-science-and-enginee… (look for the LASER project) -- Ingo Frommholz, PhD, FBCS, FHEA Reader (~Associate Professor) in Data Science Deputy Head Digital Innovations and Solutions Centre (DISC) University of Wolverhampton, UK Adjunct Professor, Bern University of Applied Sciences, Switzerland Web: http://www.frommholz.org/ | Email: ifrommholz(a)acm.org Twitter: @iFromm | Mastodon: @ingo@idf.social PGP/GPG fingerprint: B74E A422 C7B2 A5BB 2BC2 523B 2790 216E F8F8 D166 http://pgp.mit.edu:11371/pks/lookup?op=get&search=0x2790216EF8F8D166

1 0

LongEval: Call for papers and talk proposals
by Elena Kochkina 01 Jun '23

01 Jun '23

Dear colleagues, We invite submissions of papers and talk proposals to LongEval 2023 Workshop on Longitudinal Evaluation of Model Performance. https://clef-longeval.github.io/ CLEF 2023 Conference and Labs of the Evaluation Forum<https://clef2023.clef-initiative.eu/index.php> 18-21 September 2023, Thessaloniki - Greece<https://clef2023.clef-initiative.eu/index.php><https://clef2023.clef-initiative.eu/index.php> Topics of interest include (but not limited to): • Evaluations of the temporal persistence of information retrieval (IR) systems and text classifiers for various tasks • Challenges posed by the dynamic nature of language • Time-aware longitudinal models • Post-evaluation stage LongEval shared-task submissions. Deadlines: Papers: June 5th (to be included in the proceedings) Submission format: https://drive.google.com/drive/folders/1r2lNOteMNoQrhQGUat6VHPUnwFAgR8Nz Length: a maximum of 8 pages not including references and appendices). Submission link: https://easychair.org/my/conference?conf=clef2023 Talk proposals: July 10th (not included in the proceedings) Submission format: a maximum of 2 pages Submission link: https://forms.gle/fU46Fb5zJufxF5NV8 Organisers: Alkhalifa, Rabab, Bilal, Iman, Borkakoty, Hsuvas, Camacho-Collados, Jose, Deveaud, Romain, El-Ebshihy, Alaa, Espinosa-Anke, Luis, Gonzalez-Saez, Gabriela, Galusakova, Petra, Goeuriot, Lorraine, Kochkina, Elena, Liakata, Maria, Loureiro, Daniel, Tayyar Madabushi, Harish, Mulhem, Philippe, Piroi, Florina, Popel, Martin, Servan, Christophe, Zubiaga, Arkaitz. Feel free to reach out with any questions! Best regards, Elena Kochkina On behalf of LongEval organisers

1 0

Third CFP: Computational Terminology in NLP and Translation Studies (ConTeNTs)
by amalhaddad＠ugr.es 01 Jun '23

01 Jun '23

The 1st Workshop on Computational Terminology in NLP and Translation Studies (ConTeNTs) Varna, 7th-8th September, 2023 In conjunction with RANLP 2023 - International Conference "Recent Advances in Natural Language Processing" Third call for papers Computational Terminology and new technologies applied to translation studies have attracted the interest of researchers with very different multidisciplinary backgrounds and motivations. Those fields cover a range of areas in Natural Language Processing (NLP) such as information retrieval, terminology extraction, question-answering systems, ontology building, machine translation, computer-aided translation, automatic or semi-automatic abstracting, text generation, etc. Terminological identification, extraction and coinage of new terms are essential for knowledge mining from texts, both in high and low resources languages. Quick evolutions and new developments in specialised domains require efficient and systematic automatic term management. New terms need to be coined and translated to ensure the equitable development of domains in all languages. During the last decade, deep learning and neural methods have become the state of the art for most NLP applications. Those applications were shown to outperform previous methods on various tasks, including automatic term extraction, language mining, assessment of quality in machine translation, accessibility of terminology, etc. On the one hand, NLP and computational linguistics try to improve the work of translators and interpreters by developing Computer-Assisted Translation (CAT) tools, Translation Memories (TMs), terminological databases and terminology extraction tools, etc. On the other hand, the NLP field still needs the efforts and knowledge of translators, interpreters and linguists to provide better services and tools based on the real necessities of those language professionals. The aim of this workshop is to promote new insights into the ongoing and forthcoming developments in computational terminology by bringing together NLP experts, as well as terminologists and translators. By uniting researchers with such diverse profiles, we hope to bridge some of the gaps between these disciplines and inspire a dialogue between various parties, thus paving the way to more artificial intelligence applications based on mutual collaboration between language and technology. Topics of Interest The ConTeNTs workshop invites the submission of papers reporting on original and unpublished research on topics related to Computational Terminology in NLP and Translation Studies, including but not limited to: * Automatic term extraction: monolingual and multilingual extraction of terms from parallel and comparable corpora, including single and multiword expressions; * Extraction and acquisition of semantic relations between terms; * Extraction and generation of domain specific definitions and disambiguation of terms; * Representation of terms, management of term variation and the discovery of synonym terms or term clusters and its relation to NLP applications; * Extraction of terminological context, through the use of comparable and parallel corpus; * Accessibility of terminology in certain domains, relevant to non-experts or to laypersons, and its relevance to NLP applications such as, chatbots, automatic email generation or spoken language interface; * The impact of terminology on MT (applying terminology constraints, evaluation of MT in domain-specific settings, etc.); * The creation of domain ontologies, thesaurus, terminological resources in specialised domains; * The use of new technologies in translation studies and research and the use of terminological resources in specialised translation; * Identification of key problems in terminology and new technologies used in translation studies; * Evaluation of terminological resources in various NLP applications and the impact of these resources have on the performance of the automatic systems; * Emerging language technologies: how the increased reliance on real-time language technologies would change the structure of language; * Corpus based studies applied to translation and interpreting: the use of parallel and comparable corpora for translating phraseological units; * Phraseology and multiword expressions in cross-linguistic studies; * Translation and interpreting tools, such as translation memories, machine translation and alignment tools; * User requirements for interpreting and translation tools. SUBMISSION GUIDELINES Submissions must consist of full-text papers and should not exceed 7 pages excluding references, they should be a minimum of 5 pages long. The accepted papers will be published as ConTeNTs workshop e-proceedings with ISBN, will be assigned a DOI and will be also available at the time of the conference. The papers should be in English. Authors of accepted papers will receive guidelines regarding how to produce camera-ready versions of their papers for inclusion in the proceedings. Each submission will be reviewed by at least two programme committee members. Accepted papers will be presented orally as part of the programme of the workshop. Submissions Link to START system: https://softconf.com/ranlp23/ConTeNTS Website of the workshop: https://contents2023.kulak.kuleuven.be/ Should you require any assistance with the submission, please do not hesitate to contact us at amalhaddad(a)ugr.es and ayla.rigoutsterryn(a)kuleuven.be. Important Dates Deadline for paper submission: 10 July 2023 Acceptance notification: 5 August 2023 Final camera-ready version: 25 August 2023 Workshop camera-ready proceedings ready: 31 August 2023 ConTeNTs workshop: 7/8 September 2023 Workshop Chairs & Organising Committee Ayla Rigouts Terryn, Katholieke Universiteit Leuven, Belgium Amal Haddad Haddad, Universidad de Granada, Spain Ruslan Mitkov, University of Wolverhampton, United Kingdom Programme Committee * Sophia Ananiadou (University of Manchester) * Maria Andreeva Todorova (Bulgarian Academy of Sciences) * Silvia Bernardini (University of Bologna) * Melania Cabezas García (Universidad de Granada) * Rute Costa (Universidade Nova de Lisboa) * Esther Castillo Pérez (Universidad de Granada) * Patrick Drouin (Université de Montréal) * Pamela Faber (Universidad de Granada) * Mercedes García de Quesada (Universidad de Granada) * Dagmar Gromann (Centre for Translation Studies - University of Vienna) * Tran Thi Hong Hanh (L3i Laboratory, University of La Rochelle) * Rejwanul Haque (National College of Ireland) * Amir Hazem (Nantes University) * Kyo Kageura (University of Tokyo) * Barbara Karsch (BIK Terminology - USA) * Dorothy Kenny (Dublin City University) * Miloš Jakubíček (Sketch Engine) * Hendrik Kockaert (KU Leuven) * Philipp Koehn (Johns Hopkins University) * Maria Kunilovskaya (Saarland University) * Marie-Claude L'Homme (Université de Montréal) * Hélène Ledouble (Université de Toulon) * Pilar León-Araúz (Universidad de Granada) * Rodolfo Maslias (former Head of TermCoord, European Parliament) * Silvia Montero Martínez (Universidad de Granada) * Emmanuel Morin (LS2N-TALN) * Rogelio Nazar (Pontificia Universidad Católica de Valparaíso) * Sandrine Peraldi (University College Dublin) * Silvia Piccini (Italian National Research Council) * Thierry Poibeau (CNRS) * Senja Pollak (Jožef Stefan Institute) * Maria Pozzi Pardo (El Colegio de México) * Tharindu Ranasinghe (Aston University) * Arianne Reimerink (Universidad de Granada) * Andres Repar (Jožef Stefan Institute) * Christophe Roche (Université Savoie Mont-Blanc) * Antonio San Martín Pizarro (Université du Québec à Trois-Rivières) * Beatriz Sánchez Cárdenas (Universidad de Granada) * Vilelmini Sosoni (Ionian University) * Irena Spasic (Cardiff University) * Elena Isabelle Tamba (Romanian Academy, Iași Branch) * Rita Temmerman (Vrije Universiteit Brussel) * Jorge Vivaldi Palatresi (Universitat Pompeu Fabra)

1 0

PhD in ML/NLP – Efficient, Fair, robust and knowledge informed self-supervised learning for speech processing
by François Portet 01 Jun '23

01 Jun '23

PhD in ML/NLP – Efficient, Fair, robust and knowledge informed self-supervised learning for speech processing Starting date: November 1st, 2022 (flexible) Application deadline: September 5th, 2022 Interviews (tentative): September 19th, 2022 Salary: ~2000€ gross/month (social security included) Mission: research oriented (teaching possible but not mandatory) *Keywords:*speech processing, natural language processing, self-supervised learning, knowledge informed learning, Robustness, fairness *CONTEXT* The ANR project E-SSL (Efficient Self-Supervised Learning for Inclusive and Innovative Speech Technologies) will start on November 1st 2022. Self-supervised learning (SSL) has recently emerged as one of the most promising artificial intelligence (AI) methods as it becomes now feasible to take advantage of the colossal amounts of existing unlabeled data to significantly improve the performances of various speech processing tasks. *PROJECT OBJECTIVES* Recent SSL models for speech such as HuBERT or wav2vec 2.0 have shown an impressive impact on downstream tasks performance. This is mainly due to their ability to benefit from a large amount of data at the cost of a tremendous carbon footprint rather than improving the efficiency of the learning. Another question related to SSL models is their unpredictable results once applied to realistic scenarios which exhibit their lack of robustness. Furthermore, as for any pre-trained models applied in society, it isimportant to be able to measure the bias of such models since they can augment social unfairness. The goals of this PhD position are threefold: - to design new evaluation metrics for SSL of speech models ; - to develop knowledge-driven SSL algorithms ; - to propose methods for learning robust and unbiased representations. SSL models are evaluated with downstream task-dependent metrics e.g., word error rate for speech recognition. This couple the evaluation of the universality of SSL representations to a potentially biased and costly fine-tuning that also hides the efficiencyinformation related to the pre-training cost. In practice, we will seek to measure the training efficiency as the ratio between the amount of data, computation and memory needed to observe a certain gain in terms of performance on a metric of interest i.e.,downstream dependent or not. The first step will be to document standard markers that can be used as robust measurements to assess these values robustly at training time. Potential candidates are, for instance, floating point operations for computational intensity, number of neural parameters coupled with precision for storage, online measurement of memory consumption for training and cumulative input sequence length for data. Most state-of-the-art SSL models for speech rely onmasked prediction e.g. HuBERT and WavLM, or contrastive losses e.g. wav2vec 2.0. Such prevalence in the literature is mostly linked to the size, amount of data and computational resources injected by thecompany producing these models. In fact, vanilla masking approaches and contrastive losses may be identified as uninformed solutions as they do not benefit from in-domain expertise. For instance, it has been demonstrated that blindly masking frames in theinput signal i.e. HuBERT and WavLM results in much worse downstream performance than applying unsupervised phonetic boundaries [Yue2021] to generate informed masks. Recently some studies have demonstrated the superiority of an informed multitask learning strategy carefully selecting self-supervised pretext-tasks with respect to a set of downstream tasks, over the vanilla wav2vec 2.0 contrastive learning loss [Zaiem2022]. In this PhD project, our objective is: 1. continue to develop knowledge-driven SSL algorithms reaching higher efficiency ratios and results at the convergence, data consumption and downstream performance levels; and 2. scale these novel approaches to a point enabling the comparison with current state-of-the-art systems and therefore motivating a paradigm change in SSL for the wider speech community. Despite remarkable performance on academic benchmarks, SSL powered technologies e.g. speech and speaker recognition, speech synthesis and many others may exhibit highly unpredictable results once applied to realistic scenarios. This can translate into a global accuracy drop due to a lack of robustness to adversarial acoustic conditions, or biased and discriminatory behaviors with respect to different pools of end users. Documenting and facilitating the control of such aspects prior to the deployment of SSL models into the real-life is necessary for the industrial market. To evaluate such aspects, within the project, we will create novel robustness regularization and debasing techniques along two axes: 1. debasing and regularizing speech representations at the SSL level; 2. debasing and regularizing downstream-adapted models (e.g. using a pre-trained model). To ensure the creation of fair and robust SSL pre-trained models, we propose to act both at the optimization and data levels following some of our previous work on adversarial protected attribute disentanglement and the NLP literature on data sampling and augmentation [Noé2021]. Here, we wish to extend this technique to more complex SSL architectures and more realistic conditions by increasing the disentanglement complexity i.e. the sex attribute studied in [Noé2021] is particularly discriminatory. Then, and to benefit from the expert knowledge induced by the scope of the task of interest, we will build on a recent introduction of task-dependent counterfactual equal odds criteria [Sari2021] to minimize the downstream performance gap observed in between different individuals of certain protected attributes and to maximize the overall accuracy. Following this multi-objective optimization scheme, we will then inject further identified constraints as inspired by previous NLP work [Zhao2017]. Intuitively, constraints are injected so the predictions are calibrated towards a desired distribution i.e. unbiased. *SKILLS* * Master 2 in Natural Language Processing, Speech Processing, computer science or data science. * Good mastering of Python programming and deep learning framework. * Previous in Self-Supervised Learning, acoustic modeling or ASR would be a plus * Very good communication skills in English * Good command of French would be a plus but is not mandatory *SCIENTIFIC ENVIRONMENT* The thesis will be conducted within the Getalp teams of the LIG laboratory (_https://lig-getalp.imag.fr/_ <https://lig-getalp.imag.fr/>) and the LIA laboratory (https://lia.univ-avignon.fr/). The GETALP team and the LIA have a strong expertise and track record in Natural Language Processing and speech processing. The recruited person will be welcomed within the teams which offer a stimulating, multinational and pleasant working environment. The means to carry out the PhD will be providedboth in terms of missions in France and abroad and in terms of equipment. The candidate will have access to the cluster of GPUs of both the LIG and LIA. Furthermore, access to the National supercomputer Jean-Zay will enable to run large scale experiments. The PhD position will be co-supervised by Mickael Rouvier (LIA, Avignon) and Benjamin Lecouteux and François Portet (Université Grenoble Alpes). Joint meetings are planned on a regular basis and the student is expected to spend time in both places. Moreover, the PhD student will collaborate with several team members involved in the project in particular the two other PhD candidates who will be recruited and the partners from LIA, LIG and Dauphine Université PSL, Paris. Furthermore, the project will involve one of the founders of SpeechBrain, Titouan Parcollet with whom the candidate will interact closely. *INSTRUCTIONS FOR APPLYING* Applications must contain: CV + letter/message of motivation + master notes + be ready to provide letter(s) of recommendation; and be addressed to Mickael Rouvier (_mickael.rouvier(a)univ-avignon.fr_ <mailto:mickael.rouvier@univ-avignon.fr>), Benjamin Lecouteux(benjamin.lecouteux(a)univ-grenoble-alpes.fr) and François Portet (_francois.Portet(a)imag.fr_ <mailto:francois.Portet@imag.fr>). We celebrate diversity and are committed to creating an inclusive environment for all employees. *REFERENCES:* [Noé2021] Noé, P.- G., Mohammadamini, M., Matrouf, D., Parcollet, T., Nautsch, A. & Bonastre, J.- F. Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy Preservation in Proc. Interspeech 2021 (2021), 1902–1906. [Sari2021] Sarı, L., Hasegawa-Johnson, M. & Yoo, C. D. Counterfactually Fair Automatic Speech Recognition. IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 3515–3525 (2021) [Yue2021] Yue, X. & Li, H. Phonetically Motivated Self-Supervised Speech Representation Learning in Proc. Interspeech 2021 (2021), 746–750. [Zaiem2022] Zaiem, S., Parcollet, T. & Essid, S. Pretext Tasks Selection for Multitask Self-Supervised Speech Representation in AAAI, The 2nd Workshop on Self-supervised Learning for Audio and Speech Processing, 2023 (2022). [Zhao2017] Zhao, J., Wang, T., Yatskar, M., Ordonez, V. & Chang, K. - W. Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints in Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (2017), 2979–2989. -- François PORTET Professeur - Univ Grenoble Alpes Laboratoire d'Informatique de Grenoble - Équipe GETALP Bâtiment IMAG - Office 333 700 avenue Centrale Domaine Universitaire - 38401 St Martin d'Hères FRANCE Phone: +33 (0)4 57 42 15 44 Email:francois.portet@imag.fr www:http://membres-liglab.imag.fr/portet/

1 6

Call for Papers: 3rd Workshop on Computational Linguistics for the Political and Social Sciences (CPSS 2023)
by Gabriella Lapesa 31 May '23

31 May '23

Call for Papers: 3rd Workshop on Computational Linguistics for the Political and Social Sciences (CPSS 2023): https://sites.google.com/view/cpss2023konvens/home-page * Workshop description * This workshop aims at bringing together researchers and ideas from computational linguistics/NLP and the text-as-data community from political and social science to foster collaboration and catalyze further interdisciplinary research efforts between these communities. * Potential topics * - Modeling political communication with NLP (e.g. topic classification, position measurement) - Mining policy debates from heterogeneous textual sources - Modeling complex social constructs (e.g. populism, polarization, identity) with NLP methods - Political and social bias in language models - Methodological insights in interdisciplinary collaboration: workflows, challenges, best practices - Application of NLP methods to understand and support democratic decision making - Resources and tools for Political/Social Science research - … and more * Important dates * - Submission deadline: June 14, 2023 - Notification of acceptance: July 10, 2023 - Camera-ready deadline: July 20, 2023 - Workshop: September 22, 2023 The workshop is co-located with KONVENS 2023 in Ingolstadt (https://www.thi.de/konvens-2023). * Submissions * We solicit two types of submissions: - archival papers describing original and unpublished work (long papers: max. 8 pages, references/appendix excluded; short papers: max 4 pages, references/appendix excluded). Accepted papers will be published in the ACL anthology. For the submission format, refer to the KONVENS template. - non-archival papers (1-page abstracts, references excluded) describing already published research or ongoing work The two formats will meet the need of researchers from different communities, allowing the exchange of ideas in a "get to know each other" environment which we hope will foster future collaborations. For more information, please refer to the workshop website: https://sites.google.com/view/cpss2023konvens/home-page If you have any questions, please feel free to contact the workshop organizers. * Organizers * Gabriella Lapesa (U-Stuttgart) Christopher Klamm (U-Mannheim) Theresa Gessler (European University Viadrina) Valentin Gold (U-Göttingen) Simone Ponzetto (U-Mannheim)

1 0

Webminar by Pascale Fung - The Hong Kong University of Science and Technology (additional information)
by HiTZ zentroa 31 May '23

31 May '23

**** We apologize for the multiple copies of this email. In case you are already registered to the next webinar, you do not need to register again. **** Dear colleague, We are happy to announce the next webinar in the Language Technology webinar series organized by the HiTZ research center (Basque Center for Language Technology, http://hitz.eus). This will be the final webinar of this academic year. You can check the videos of previous webinars and the schedule for upcoming webinars here: http://www.hitz.eus/webinars Next webinar: * *Speaker*: Pascale Fung (The Hong Kong University of Science and Technology) * *Title*: Safer Generative ConvAI * *Date*: Jun 1, 2023, 15:00 CET * *Summary*: Generative models for Conversational AI are less than a decade old, but they hold great promise for human-machine interactions. Machine responses based on generative models can seem quite fluent and human-like, empathetic and funny, knowledgeable and professional. However, behind the confident voice of generative ConvAI systems, they can also be hallucinating misinformation, giving biased and harmful views, and are still not "safe" enough for many real life applications. The expressive power of generative ConvAI models and their undesirable behavior are two sides of the same coin. How can we harness the fluency, diversity, engagingness of generative ConvAI models while mitigating the downside? In this talk, I will present some of our team’s recent work in making generative ConvAI safer via mitigating hallucinations, misinformation, and toxicity. * *Bio*: Pascale Fung is a Chair Professor at the Department of Electronic & Computer Engineering at The Hong Kong University of Science & Technology (HKUST), and a visiting professor at the Central Academy of Fine Arts in Beijing. She is an elected Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) for her "significant contributions to the field of conversational AI and to the development of ethical AI principles and algorithms", an elected Fellow of the Association for Computational Linguistics (ACL) for her “significant contributions towards statistical NLP, comparable corpora, and building intelligent systems that can understand and empathize with humans”. She is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE) for her “contributions to human-machine interactions” and an elected Fellow of the International Speech Communication Association for “fundamental contributions to the interdisciplinary area of spoken language human-machine interactions”. She is the Director of HKUST Centre for AI Research (CAiRE). She was the founding chair of the Women Faculty Association at HKUST. She is an expert on the Global Future Council, a think tank for the World Economic Forum. She represents HKUST on Partnership on AI to Benefit People and Society. She is on the Board of Governors of the IEEE Signal Processing Society. She is a member of the IEEE Working Group to develop an IEEE standard - Recommended Practice for Organizational Governance of Artificial Intelligence. Her research team has won several best and outstanding paper awards at ACL, ACL and NeurIPS workshops. 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

1 0

UK PhD Studentship in Mining Electronic Health Records to Identify Effective Dietetic Factors
by Shangming Zhou 31 May '23

31 May '23

*Mining Routinely Collected Electronic Health Records to Identify Effective Dietetic Factors for Optimal Care in General Practice* DoS: Professor Shang-Ming Zhou (shangming.zhou(a)plymouth.ac.uk, tel.: 01752 586513) 2nd Supervisor: Professor Mary Hickson (mary.hickson(a)plymouth.ac.uk , tel.: 01752 587542) 3rd Supervisor: Dr Avril Collinson (avril.collinson(a)plymouth.ac.uk, tel.: 01752 588848) Applications are invited for a three-year PhD studentship. The studentship will start on 1st October 2023 or 01 January 2024 for the right candidate. *Project Description* The typical approach to dietetic work in primary care involves outreach clinics and educational initiatives that are provided by dietitians working in community or acute settings, or by offering dietetic clinics inside GP offices taking referrals from GPs. More recently, dietitians have been able to train to become first contact practitioners; a diagnostic clinician able to assess and manage undifferentiated and undiagnosed presentations. However, the ways in which these practitioners operate has yet to be defined and the role in dietetics is in its infancy and requires evaluation. The aims of this project are to interrogate multiples electronic health databases and build evidence on dietetic care in general practice. This study will enable the definition of what areas of general practice workload a dietitian can support and build evidence of dietary factors that influence disease risk and patterns of risk stratification. The funded PhD student will use statistics and machine learning techniques with data extracted from the electronic health records to generate evidence on dietetic care. *Eligibility* Applicants should have 1. A first or upper second-class honours degree in an appropriate subject or a relevant Masters qualification in Health Informatics, Medical Informatics, Bioinformatics, Health Data Science, Computing Science, Statistics, or any areas related; 2. Interest in working with real-world problems and large data sets; 3. Excellent proficiency in English and outstanding communication skills; 4. Strong analytical and programming skills; 5. A “can do”, positive attitude with an aspiration to change the world. - Experience in machine learning is advantageous. - Experience in publication of peer-reviewed literature is desirable. If your first language is not English, you will need to meet the minimum English requirements for the programme, academic IELTS score of 6.5 or above (with no less than 5.5 in each component test area) or equivalent. *Funding* *To view the funding details*, please visit here <https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/postg…> . If you wish to discuss this project further informally, please contact Professor Shang-Ming Zhou <https://www.plymouth.ac.uk/staff/shang-ming-zhou> via shangming.zhou(a)plymouth.ac.uk *To apply for this position *please click 'Apply' above. *Please clearly state the name of the DoS and the studentship title that you are applying for on the top of your Personal Statement.* Please see here <https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/appli…> for a list of supporting documents to upload with your application. - *Provision of a research proposal is advantageous.* For more information on the admissions process generally, please visit our How to Apply for a Research Degree <https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/appli…> webpage or contact the Doctoral College <doctoral.college(a)plymouth.ac.uk>. *The closing date for applications is 12 noon on 31st July 2023.* Shortlisted candidates will be invited for interview shortly after the deadline. We regret that we may not be able to respond to all applications. Applicants who have not received a response within six weeks of the closing date should consider their application has been unsuccessful on this occasion. Funding Notes The studentship is supported for 3 years and includes full Home tuition fees plus a stipend of £17,668 per annum 2022/23 rate (2023/24 rate TBC). The studentship will only fully fund those applicants who are eligible for Home fees with relevant qualifications. Applicants normally required to cover International fees will have to cover the difference between the Home and the International tuition fee rates (approximately £12,697 per annum). NB: The studentship is supported for three years of the four-year registration period. The fourth year is a self-funded ‘writing-up’ year.

1 0

2026

2025

2024

2023

2022

Corpora