== 11th NLP4CALL, Louvain-la-Neuve, Belgium==
The workshop series on Natural Language Processing (NLP) for Computer-Assisted Language Learning (NLP4CALL) is a meeting place for researchers working on the integration of Natural Language Processing and Speech Technologies in CALL systems and exploring the theoretical and methodological issues arising in this connection. The latter includes, among others, insights from Second Language Acquisition (SLA) research, on the one hand, and promote development of "Computational SLA" through setting up Second Language research infrastructure(s), on the other.
The intersection of Natural Language Processing (or Language Technology / Computational Linguistics) and Speech Technology with Computer-Assisted Language Learning (CALL) brings "understanding" of language to CALL tools, thus making CALL intelligent. This fact has given the name for this area of research – Intelligent CALL, ICALL. As the definition suggests, apart from having excellent knowledge of Natural Language Processing and/or Speech Technology, ICALL researchers need good insights into second language acquisition theories and practices, as well as knowledge of second language pedagogy and didactics. This workshop invites therefore a wide range of ICALL-relevant research, including studies where NLP-enriched tools are used for testing SLA and pedagogical theories, and vice versa, where SLA theories, pedagogical practices or empirical data are modeled in ICALL tools.
The NLP4CALL workshop series is aimed at bringing together competences from these areas for sharing experiences and brainstorming around the future of the field.
We welcome papers:
- that describe research directly aimed at ICALL;
- that demonstrate actual or discuss the potential use of existing Language and Speech Technologies or resources for language learning;
- that describe the ongoing development of resources and tools with potential usage in ICALL, either directly in interactive applications, or indirectly in materials, application or curriculum development, e.g. learning material generation, assessment of learner texts and responses, individualized learning solutions, provision of feedback;
- that discuss challenges and/or research agenda for ICALL
- that describe empirical studies on language learner data.
This year a special focus is given to work done on second language vocabulary and grammar profiling, as well as the use of crowdsourcing for creating, collecting and curating data in NLP projects.
We encourage paper presentations and software demonstrations describing the above-mentioned themes primarily, but not exclusively, for the Nordic languages.
==Invited speakers==
This year, we have the pleasure to announce two invited talks.
The first talk is by Christopher Bryant from Reverso and the University of Cambridge.
The second talk is given by Marije Michel from the University of Amsterdam.
==Submission information==
Authors are invited to submit long papers (8-12 pages) alternatively short papers (4-7 pages), page count not including references. We will be using the NLP4CALL workshop template for the workshop this year. The author kit, including LaTeX and Microsoft Word templates can be accessed here, alternatively on Overleaf:
<https://spraakbanken.gu.se/sites/default/files/2022/NLP4CALL%20workshop%20t…>
<https://spraakbanken.gu.se/sites/default/files/2022/nlp4call%20template.doc>
<https://www.overleaf.com/latex/templates/nlp4call-workshop-template/qqqzqqy…>
Submissions will be managed through the electronic conference management system EasyChair <https://easychair.org/conferences/?conf=nlp4call2022>. Papers must be submitted digitally through the conference management system, in PDF format. Final camera-ready versions of accepted papers will be given an additional page to address reviewer comments.
Papers should describe original unpublished work or work-in-progress. Papers will be peer reviewed by at least two members of the program committee in a double-blind fashion. All accepted papers will be collected into a proceedings volume to be submitted for publication in the NEALT Proceeding Series (Linköping Electronic Conference Proceedings) and, additionally, double-published through the ACL anthology, following experiences from the previous NLP4CALL editions (<https://www.aclweb.org/anthology/venues/nlp4call/>).
==Important dates==
7 October 2022: paper submission deadline
4 November 2022: notification of acceptance
25 November 2022: camera-ready papers for publication
9 December 2022: workshop date
==Organizers==
David Alfter (1,2), Elena Volodina (2), Thomas François (1), Piet Desmet (3), Frederik Cornillie (3), Arne Jönsson (4), Eveline Rennes (4)
(1) CENTAL, Institute for Language and Communication, Université Catholique de Louvain, Belgium
(2) Språkbanken, University of Gothenburg, Sweden
(3) Itec, Department of Linguistics at KU Leuven & imec, Belgium
(4) Department of Computer and Information Science, Linköping University, Sweden
==Contact==
For any questions, please contact David Alfter, david.alfter(a)uclouvain.be
For further information, see the workshop website <https://spraakbanken.gu.se/en/research/themes/icall/nlp4call-workshop-serie…>
Follow us on Twitter @NLP4CALL <https://twitter.com/NLP4CALL/>
David Alfter, PhD
Post-doctoral researcher
Institut Langage et communication, CENTAL
Université catholique de Louvain
Place Montesquieu, 3 (box L2.06.04)
1348 Louvain-la-Neuve
The Austrian Research Institute for Artificial Intelligence (OFAI) is
delighted to announce its 2022 Lecture Series, featuring an eclectic
lineup of internal and external speakers.
The talks are intended to familiarize attendees with the latest research
developments in AI and related fields (particularly computational
linguistics and natural language processing), and to forge new
connections with those working in other areas.
Most lectures (see prospective schedule below) will take place on
Wednesdays at 18:30 Central European (Summer) Time. All lectures will be
held online via Zoom; in-person attendance at OFAI Headquarters in
Vienna is also possible for certain lectures.
Attendance is open to the public and free of charge. No registration is
required.
Visit https://www.ofai.at/lectures for full details!
29 June
Scott Patterson
McGill University
Domesticating Wealth Inequality: Hybrid Discourse Analysis of UN General
Assembly Speeches, 1971–2018
6 July
Pamela Breda
Independent artist
Feeling for Nonexsistent Beings
13 July
Brigitte Krenn
OFAI
Robots as Social Agents: Between Construct and Reality
20 July
Tristan Miller
OFAI
What's in a Pun? Assessing the Relationship Between Phonological and
Semantic Distance and Perceived Funniness of Punning Jokes
27 July
Katrien Beuls
Université de Namur
Unravelling the Computational Mechanisms Underlying the Emergence of
Human-like Communication Systems in Populations of Autonomous Agents
7 September
Steffen Eger
Bielefeld University
Text Generation for the Humanities
14 September
Antti Arppe
University of Alberta
Finding Words that Aren't There: Using Word Embeddings to Improve
Dictionary Search for Low-resource Languages
21 September
Roman Pflugfelder
AIT Austrian Institute of Technology
Title TBA
28 September
Raphael Deimel
TU Wien
Towards Intuitive Object Handovers Between Humans and Robots
5 October
Christoph Scheepers
University of Glasgow
The “Crossword Effect” in Free Word Recall: A Retrieval Advantage for
Words Encoded in Line with their Spatial Associations
12 October
Karën Fort
Sorbonne Université
Title TBA
19 October
Benjamin Roth
University of Vienna
Evaluation and Learning with Structured Test Sets
25 October
Peter Hallman
OFAI
Comparatives in Arabic
2 November
Stephanie Gross
OFAI
Title TBA
9 November
Bernhard Pfahringer
University of Waikato
The World is not IID: Learning from Data Streams to the Rescue
16 November
Paolo Petta
OFAI
Title TBA
23 November
Robert Trappl
OFAI
Title TBA
--
Dr.-Ing. Tristan Miller, Research Scientist
Austrian Research Institute for Artificial Intelligence (OFAI)
Freyung 6/6, 1010 Vienna, Austria | Tel: +43 1 5336112 12
https://logological.org/ | https://punderstanding.ofai.at/
*** First Workshop on Information Extraction from Scientific Publications (
WIESP) at AACL-IJCNLP 2022 ***
*** Website: https://ui.adsabs.harvard.edu/WIESP/
*** Twitter: https://twitter.com/wiesp_nlp
The number of scientific papers published per year has exploded in recent
years. Indexing the article's full text in search engines helps discover
and retrieve vital scientific information to continue building on the
shoulders of giants, informing policy, and making evidence-based decisions.
Nevertheless, it is difficult to navigate this ocean of data. Using simple
string matching has substantial limitations: human language is ambiguous in
nature, context matters, and we frequently use the same word and acronyms
to represent a multitude of different meanings. Extracting structured and
semantically relevant information from scientific publications (e.g.,
named-entity recognition, summarization, citation intention, linkage to
knowledge graphs) allows for better selection and filter articles.
The First Workshop on Information Extraction from Scientific Publications (
WIESP) will create the necessary forum to foster discussion and research
using Natural Language Processing and Machine Learning. WIESP would
specifically focus on topics related to information extraction from
scientific publications, including (but not limited to):
- Scientific document parsing
- Scientific named-entity recognition
- Scientific article summarization
- Question-answering on scientific articles
- Citation context/span extraction
- Structured information extraction from full-text, tables, figures,
bibliography
- Novel datasets curated from scientific publications
- Argument extraction and mining
- Challenges in information extraction from scientific articles
- Building knowledge graphs via mining scientific literature; querying
scientific knowledge graphs
- Novel tools for IE on scientific literature and interaction with users
- Mathematical information extraction
- Scientific concepts, facts extraction
- Visualizing scientific knowledge
- Bibliometric and Altmetric studies via information extraction from
scientific articles and metadata
- Information extraction from COVID-19 articles to inform public health
policy
In addition to research paper presentations, WIESP would also feature
keynote talks, a panel discussion, and a shared task. We will update the
details on our website as and when they become available. We especially
welcome participation from academic and research institutions, government
and industry labs, publishers, and information service providers. Projects
and organizations using NLP/ML techniques in their text mining and
enrichment efforts are also welcome to participate.
***Call for Papers***
We invite papers of the following categories:
***Long papers*** must describe substantial, original, completed, and
unpublished work. Wherever appropriate, concrete evaluation and analysis
should be included. Papers must not exceed eight (8) pages of content, plus
unlimited pages of references. The final versions of long papers will be
given one additional page of content (up to 9 pages) so that reviewers'
comments can be taken into account.
***Short papers*** must describe original and unpublished work. Please note
that a short paper is not a shortened long paper. Instead, short papers
should have a point that can be made in a few pages, such as a small,
focused contribution, a negative result, or an interesting application
nugget. Short papers must not exceed four (4) pages, plus unlimited pages
of references. The final versions of short papers will be given one
additional page of content (up to 5 pages) so that reviewers' comments can
be taken into account.
***Position papers*** will give voice to authors who wish to take a
position on a topic listed above or the field of scholarly information
extraction. Submissions need not present original work and should be two to
four pages in length, including title, text, figures and tables, and
references.
***Demo papers*** should be no more than four (4) pages in length,
including references, and should describe implemented systems that are of
relevance to the theme of the workshop. Authors of demo papers should be
willing to present a demo of their system during WIESP at AACL-IJCNLP 2022.
***Extended Abstracts*** We welcome submissions of extended abstracts (2
pages max) related to the research topics mentioned above. Submissions may
include previously published results, late-breaking results, or a
description of ongoing projects in the broad field of information
extraction and mining from scientific publications. Extended abstracts can
also summarize existing work, work in progress, or a collection of works
under a unified theme (e.g., a series of closely related papers that build
on each other or tackle a common problem).
***Shared Task: Detecting Entities in the Astrophysics Literature (DEAL)***
A good amount of astrophysics research makes use of data coming from
missions and facilities such as ground observatories in remote locations or
space telescopes, as well as digital archives that hold large amounts of
observed and simulated data. These missions and facilities are frequently
named after historical figures or use some ingenious acronym which,
unfortunately, can be easily confused when searching for them in the
literature via simple string matching. For instance, Planck can refer to
the person, the mission, the constant, or several institutions.
Automatically recognizing entities such as missions or facilities would
help tackle this word sense disambiguation problem.
The shared task consists of Named Entity Recognition (NER) on samples of
text extracted from astrophysics publications. The labels were created by
domain experts and designed to identify entities of interest to the
astrophysics community. They range from simple to detect (ex: URLs) to
highly unstructured (ex: Formula), and from useful to researchers (ex:
Telescope) to more useful to archivists and administrators (ex: Grant).
Overall, 31 different labels are included, and their distribution is highly
unbalanced (ex: ~100x more Citations than Proposals). Submissions will be
scored using both the CoNLL-2000 shared task seqeval F1-Score at the entity
level and scikit-learn's Matthews correlation coefficient method at the
token level. We also encourage authors to propose their own evaluation
metrics. A sample dataset and more instructions can be found at:
https://ui.adsabs.harvard.edu/WIESP/2022/SharedTasks
Participants (individuals or groups) will have the opportunity to present
their findings during the workshop and write a short paper. The best
performant or interesting approaches might be invited to further
collaborate with the NASA Astrophysical Data System (
https://ui.adsabs.harvard.edu/).
***Important Dates***
- Paper/Abstract Submission Deadline: August 25, 2022
- Notification of workshop paper/abstract acceptance: September 25, 2022
- Camera-ready Submission Deadline: October 10, 2022
- Workshop: November 20, 2021 (online)
***All submission deadlines are 11.59 pm UTC -12h ("Anywhere on Earth")***
***Submission Website and Format***
Submission Link: softconf.com/aacl2022/WIESP
Submission will be via softconf. Submissions should follow the ACLPUB
formatting guidelines (https://acl-org.github.io/ACLPUB/formatting.html)
and template files (https://github.com/acl-org/acl-style-files/tree/master).
Submissions (Long and Short Papers) will be subject to a double-blind
peer-review process. Position papers, Demo papers, and Extended Abstracts
need not be anonymized. The authors will present accepted papers at the
workshop either as a talk or a poster. All accepted papers will be
published in the workshop proceedings.
We follow the same policies as AACL-IJCNLP 2022 regarding preprints and
double submissions. The anonymity period for WIESP 2022 is from July 15 to
September 25.
***Organizers***
- Tirthankar Ghosal, Charles University, CZ
- Sergi Blanco-Cuaresma, Center for Astrophysics | Harvard & Smithsonian,
USA
- Alberto Accomazzi, Center for Astrophysics | Harvard & Smithsonian, USA
- Robert M. Patton, Oak Ridge National Laboratory, USA
- Felix Grezes, Center for Astrophysics | Harvard & Smithsonian, USA
- Thomas Allen, Center for Astrophysics | Harvard & Smithsonian, USA
--
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Tirthankar Ghosal
Researcher at UFAL, Charles University, CZ
https://member.acm.org/~tghosal
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Call for papers for the International Journal of Learner Corpus Research (Benjamins):
Special issue on Cumulative knowledge building and replication in Learner Corpus Research
Guest editors: Tove Larsson & Doug Biber (Northern Arizona University)
Compared to other subfields of linguistics, Learner Corpus Research (LCR) has a relatively short history. For this and other reasons, most of the studies that get published in the field are exploratory in nature and focus on topics that have yet to receive prolonged attention. Such studies no doubt make valuable contributions to the field. However, LCR is arguably mature enough as a field to also have accumulated enough knowledge on certain topics for researchers to be able to instead adopt a cumulative approach.
In the cumulative approach to knowledge building, individual studies are viewed as building blocks, carefully pieced together to help us form an increasingly better understanding of a topic. There are three distinguishing characteristics of this approach: First, the literature review focuses on what we have actually learned from previous research on the topic, rather than merely cataloging individual studies. Second, the research ‘gap’ refers to an important missing element in our cumulative knowledge, rather than to a research angle that has not been explored yet; that is, the literature review is used to identify a missing piece in an existing puzzle, rather than to justify starting a new one. And finally, results of the new study are explicitly compared to previous findings, to discuss the state of our knowledge based on all studies taken together. Through this big-picture thinking, we can collectively refine our understanding of the topic, and further our knowledge in a systematic matter. Put differently, this approach enables us to build a state-of-the-art in the field by moving beyond the results of individual studies.
With this call, we invite studies of two kinds:
* Empirical studies that set out to test hypotheses arrived at from an existing body of research with the explicit aim of adding to our knowledge on a given topic that has received ample attention in LCR. Examples of topics that may be ripe for studies of this kind include, but are not limited to, linguistic complexity and the formulaic nature of learner language.
* Empirical studies that replicate findings from an existing body of research and, importantly, that focus on strengthening and/or tweaking existing generalizations in LCR. Examples of topics include, but are not limited to, claims of the spoken-like nature of learners’ written production.
Timeline:
* August 1, 2022: Abstract and title due
* September 1, 2022: Authors are notified
* September 1, 2023: Full manuscript due
Please send submissions to tove.larsson(a)nau.edu<mailto:tove.larsson@nau.edu>
---
Tove Larsson, Ph.D.
Assistant Professor of Applied Linguistics
English Department
Northern Arizona University
https://tovelarssoncl.wordpress.com
*EmoThreat: Emotions & Threat Detection in Urdu*
CICLing 2022 track @FIRE 2022*
Website: Link
<https://sites.google.com/view/multi-label-emotionsfire-task/home>
Registration is now open: Link
<https://docs.google.com/forms/d/e/1FAIpQLSfWSPSM5wlgkucnhq3lDEsnWdaitwfq2EF…>
The training set is now available. Participants are invited to publish
Working Notes of FIRE 2022*
*Task Description*
With the growth of spread and importance of social media platforms, the
effect of their misuse became more and more impactful. In particular,
numerous posts contain abusive language towards certain users and hence
worsen users’ experience from communication via such platforms, while other
posts contain actual threats that potentially put platform users in danger.
The Urdu language has more than 230 million speakers worldwide with vast
representation on social networks and digital media.
We encourage participants to participate in *EmoThreat: Emotion and Threat
detection in Urdu (Nastaliq)*
*Task A: Multi-label emotion classification in Urdu *Link
<https://sites.google.com/view/multi-label-emotionsfire-task/home/task-a>
Task A requires you to classify the tweet as one, or more of the six basic
emotions (plus neutral) which is the best representation of the emotion of
the person tweeting.
*Task B: Threatening Language Detection Task in Urdu *Link
<https://sites.google.com/view/multi-label-emotionsfire-task/home/task-b>
Task B focuses on detecting Threatening language using Twitter tweets in
Urdu language. This is a binary classification task in which participating
systems are required to classify tweets into two classes, namely:
Threatening and Non-Threatening.
*Note: Participants in this year’s shared task can choose to participate in
either one or both subtasks. Please visit the website for more information.*
*Important Dates*
30th June – Training data release
25th July – Codalab submission link release (Task A)
31st August - Test set release (Task B)
10th September – Run submission deadline
17th September – Results declared
12th October - Working Note submission
26th October - Review Notifications
2nd November – Camera Ready Due
9th - 13th December - FIRE 2022 (Online Event)
*Organizers*
Sabur Butt, Instituto Politécnico Nacional, Mexico
Maaz Amjad, Instituto Politécnico Nacional, Mexico
Noman Ashraf, Mayo Clinic Arizona, United States
Fazlourrahman Balouchzahi, Instituto Politécnico Nacional, Mexico
Rajesh Sharma, University of Tartu, Estonia
Grigori Sidorov, Instituto Politécnico Nacional, Mexico
Alexander Gelbukh, Instituto Politécnico Nacional, Mexico
*Contact*
Email: emothreat2022(a)gmail.com
Google-group: Link <https://groups.google.com/g/emothreat>
*FIRE 2022: Link <http://fire.irsi.res.in/fire/2022/home>
--
Sabur Butt
*IPN - Computer Research Center*
Link to the call: https://www.hiit.fi/open-positions/
Projects in the call: https://www.hiit.fi/artificial-intelligence-projects/
Deadline: 21 August at 11:59 pm UTC+3
The University of Helsinki is opening a position for a post-doctoral researcher as part of the EU project on High-Performance Language Technologies (HPLT). HPLT is a new EU-Horizon project in collaboration with 5 European universities (Prague, Edinburgh, Oslo, Turku and Helsinki), 2 HPC centers (in Norway and the Czech Republic) and one Spanish LT company on the development of language and translation models at scale. We propose a language data space and sustainable procedures to lower barriers to train large and competitive NLP models. The project focuses on multilinguality, reproducibility and openness. We will use modern high-performance compute infrastructures for scalable integration of data, code and models and we will create frameworks that are at the forefront of AI with language data.
Reach out for more information and feel free to forward this message.
Thank you!
--
*****************************************************************
Jörg Tiedemann
Language Technology https://blogs.helsinki.fi/language-technology/
University of Helsinki
Associate professorship or tenure-track assistant professorship in Computational Linguistics and Natural Language Processing
================================================================================================
The Department of Nordic Studies and Linguistics, Faculty of Humanities, University of Copenhagen (UCPH), Denmark, invites applications for an associate professorship or a tenure-track assistant professorship in computational linguistics and natural language processing (NLP) to be filled by December 1st, 2022, or as soon as possible thereafter.
The successful candidate will be attached to the Centre for Language Technology (CST), see Center for Sprogteknologi - Københavns Universitet (ku.dk)<javascript:void(0)>. CST conducts research in different areas of language technology, such as computational linguistics and natural language processing (NLP), language technology resources and the infrastructure around them, multimodal communication, computational cognitive modelling, digital humanities, and machine learning applied to NLP. The Centre has a strong international profile, at the same time as pursuing the development of language technology methods and resources for the Danish language. CST has considerable experience managing international research projects, frequently attracts visiting researchers and has organised major conferences in the field. Together with the Department of Computer Science of the University of Copenhagen, it offers an international MSc programme in IT and Cognition. The programme, which currently admits about 30 students a year, offers a range of courses in the areas of NLP, computer science, and cognitive
Job requirements and content
The candidate must demonstrate:
· A research record in the field of computational linguistics and NLP
· Knowledge of and experience with machine learning and deep learning methods applied to the study of language
· Programming skills, preferably using Python
· Relevant teaching experience at university level.
The following qualifications constitute additional strengths:
· A demonstrated interest in linguistics
· Interest in and experience with human language technology applications
The successful candidate will engage in cutting-edge research in computational linguistics and NLP in collaboration with the CST researchers and is expected to contribute actively to the Centre's research environment. The candidate will also be expected to strengthen the Centre's project portfolio by applying for external funding for research and development.
Furthermore, the candidate will contribute with teaching to the MSc in IT and Cognition. More specifically, the candidate is expected to contribute to the Language Processing courses and to supervise students for thesis and electives projects within computational linguistics and NLP.
For details about the qualification requirements and the application procedure: https://candidate.hr-manager.net/ApplicationInit.aspx?cid=1307&ProjectId=15…
For further information about the position, please contact Head of Department, Anne Jensen, e-mail: annejensen(a)hum.ku.dk<javascript:void(0)> or Deputy Head of Department for research Bolette S. Pedersen, bspedersen(a)hum.ku.dk<javascript:void(0)>.
The closing date for applications is 1 August 2022 at 23:59 [*CEST/CET]
·
Costanza Navarretta
PhD, senior researcher/assoc.professor
Centre for Language Technology
Department of Nordic Studies and Linguistics
University of Copenhagen
DIR +45 35329079
costanza(a)hum.ku.dk<mailto:costanza@hum.ku.dk>
Dear all,
It is time to elect SIGSEM officers for the next three-year term.
Candidates will be nominated via the SIGSEM mailing list [1].
If you would like to take part in the nomination and election process, make
sure to be registered in the SIGSEM mailing list with the email address you
check regularly.
Best,
Raffaella
On Behalf of SIGSEM Board
[1] http://www.sigsem.org/wiki/index.php?title=Join_SIGSEM
==============================================================
University of Trento
CIMeC: C225, second floor, Corso Bettini 31, 38068 Rovereto (TN),
DISI: Povo 2, Room: 110, Via Sommarive 9, I 38123, Povo (TN)
Tel. +39 0464 80 8704 (CIMeC)
http://disi.unitn.it/~bernardi/
==============================================================
***2nd SummDial: A SemDial 2022 <https://semdial2022.github.io/#> Special
Session on Summarization of Dialogues and Multi-Party Meetings***
***Website: https://elitr.github.io/automatic-minuting/summdial-2022.html
***
***Submission Deadline: August 1, 2022 ***
***Event Date: August 24, 2022 ***
With a sizeable working population of the world going virtual, resulting in
information overload from multiple online meetings, imagine how convenient
it would be to just hover over past calendar invites and get concise
summaries of the meeting proceedings? How about automatically minuting a
multimodal multi-party meeting? Are minutes and multi-party dialogue
summaries the same? We believe Automatic Minuting is challenging. There are
possibly no agreed-upon guidelines for taking minutes, and people adopt
different styles to record meeting minutes. The minutes also depend on the
meeting's category, the intended audience, and the goal or objective of the
meeting. We hosted the First SummDial Special Session at SIGDial 2021.
Several significant problems and challenges in multi-party dialogue and
meeting summarization came from the discussions in the first SummDial,
which we documented in our event report
<https://dl.acm.org/doi/10.1145/3527546.3527561>.
Since we witnessed enthusiastic participation of the dialogue and
summarization community in the first SummDial special session
<https://elitr.github.io/automatic-minuting/summdial.html> (
https://elitr.github.io/automatic-minuting/summdial.html), we are hosting
the Second SummDial special session at SemDial 2022
<https://semdial2022.github.io/#> (https://semdial2022.github.io/#). This
year, we intend to continue discussing these challenges and lessons learned
from the previous SummDial. Our goal for this special session would be to
stimulate intense discussions around this topic and set the tone for
further interest, research, and collaboration in both Speech and Natural
Language Processing communities. Our topics of interest are Dialogue
Summarization, including but not limited to Meeting Summarization, Chat
Summarization, Email Threads Summarization, Customer Service Summarization,
Medical Dialogue Summarziation, and Multi-modal Dialogue Summarization. Our
shared task on Automatic Minuting (AutoMin) at Interspeech 2021 was another
community effort in this direction. Our shared task on Automatic Minuting
(AutoMin) <https://elitr.github.io/automatic-minuting/> at Interspeech 2021
<https://www.interspeech2021.org/> was another community effort in this
direction.
***Call for papers***
We invite regular and work-in-progress papers that report:
-
Current research in multi-party dialogue summarization for summarizing
meetings, spoken dialogue, using speech, text, or multi-modal data (audio,
video),
-
Challenges in dialogue summarization evaluation (manual + automatic),
-
New methods and metrics for dialogue summarization evaluation,
-
Relevant corpus collection, pre-processing, development, and ethical
issues involved,
-
Compare and contrast speech-specific systems to systems imported from
text summarization,
-
Tools for meeting transcript generation and automatic summarization,
-
Topic detection and span identification in meeting transcripts for
multi-topic summarization,
-
Position papers to reflect on the current state of the art in this
topic, to take stock of where we have been, where we are, where we are
going and where we should go.
Researchers may choose to submit:
-
***Long papers*** Authors should submit an anonymous paper of at most 8
pages of content (up to 2 additional pages are allowed for references).
-
***Short papers*** Authors should submit a non-anonymized paper of at
most 2 pages of content (up to 1 additional page allowed for references).
Submissions to this track can be non-archival on request.
-
***Position Papers*** Including extended abstracts, work-in-progress,
and late-breaking papers.
***Submission Link***
https://easychair.org/my/conference?conf=summdial2022
Submissions should follow the ACL format. Papers that have been or will be
submitted to other meetings or publications must provide this information
using a footnote on the title page of the submissions. SummDial 2022 cannot
accept work for a publication that will be (or has been) published
elsewhere.
***Special Session Program***
The special session would consist of a keynote, a panel, oral and/or poster
paper presentations.
***Organizers***
-
Tirthankar Ghosal <https://elitr.eu/tirthankar-ghosal/>, Institute of
Formal and Applied Linguistics, Charles University, Czech Republic
-
Muskaan Singh, IDIAP, Switzerland
-
Xinnou Xu, University of Edinburgh, UK
- Ondřej Bojar <https://ufal.mff.cuni.cz/ondrej-bojar>, Institute of
Formal and Applied Linguistics, Charles University, Czech Republic
--
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Tirthankar Ghosal
Researcher at UFAL, Charles University, CZ
https://member.acm.org/~tghosal
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++