Dear all,
Apologies for cross-posting. You are requested to please circulate it for
wider publicity.
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The 5th Workshop on Technologies for Machine Translation of
Low Resource Languages (LoResMT 2022)
https://sites.google.com/view/loresmt
@ COLING 2022
Gyeongju, Republic of Korea, October 12-17, 2022
SUBMISSION
https://www.softconf.com/coling2022/LoResMT_2022/
TIMELINE
Papers Due: July 18, 2022 (Monday)
Notification of Acceptance: August 22, 2022 (Monday)
Camera-ready papers due: September 5, 2022 (Monday)
Conference date: October 12-17, 2022
SCOPE
Based on the success of past low-resource machine translation (MT)
workshops at AMTA 2018 (https://amtaweb.org/), MT Summit 2019 (
https://www.mtsummit2019.com), AACL-IJCNLP 2020 (http://aacl2020.org/), and
AMTA 2021, we introduce the Fifth LoResMT workshop at COLING 2022. The
workshop provides a discussion panel for researchers working on MT
systems/methods for low-resource and under-represented languages in
general. We would like to help review/overview the state of MT for
low-resource languages and define the most important directions. We also
solicit papers dedicated to supplementary NLP tools that are used in any
language and especially in low-resource languages. Overview papers of these
NLP tools are very welcome. It will be beneficial if the evaluations of
these tools in research papers include their impact on the quality of MT
output.
TOPICS
We are highly interested in (1) original research papers, (2)
review/opinion papers, and (3) online systems on the topics below; however,
we welcome all novel ideas that cover research on low-resource languages.
- COVID-related corpora, their translations and corresponding NLP/MT systems
- Neural machine translation for low-resource languages
- Work that presents online systems for practical use by native speakers
- Word tokenizers/de-tokenizers for specific languages
- Word/morpheme segmenters for specific languages
- Alignment/Re-ordering tools for specific language pairs
- Use of morphology analyzers and/or morpheme segmenters in MT
- Multilingual/cross-lingual NLP tools for MT
- Corpora creation and curation technologies for low-resource languages
- Review of available parallel corpora for low-resource languages
- Research and review papers of MT methods for low-resource languages
- MT systems/methods (e.g. rule-based, SMT, NMT) for low-resource languages
- Pivot MT for low-resource languages
- Zero-shot MT for low-resource languages
- Fast building of MT systems for low-resource languages
- Re-usability of existing MT systems for low-resource languages
- Machine translation for language preservation
SUBMISSION INFORMATION
We are soliciting two types of submissions: (1) research, review, and
position papers and (2) system demonstration papers. For research, review
and position papers, the length of each paper should be at least four (4)
and not exceed eight (8) pages, plus unlimited pages for references. For
system demonstration papers, the limit is four (4) pages. Submissions
should be formatted according to the official COLING 2022 style templates
(LaTeX, Word, Overleaf). Accepted papers will be published online in the
COLING 2022 proceedings and will be presented at the conference.
Submissions must be anonymized and should be done using the official
conference management system (
https://www.softconf.com/coling2022/LoResMT_2022/). 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
LoResMT. 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 is handled by the main conference (
https://coling2022.org/coling).
ORGANIZING COMMITTEE (LISTED ALPHABETICALLY)
Atul Kr. Ojha, DSI, National University of Ireland Galway & Panlingua
Language Processing LLP
Chao-Hong Liu, Potamu Research Ltd
Ekaterina Vylomova, University of Melbourne, Australia
Jade Abbott, Retro Rabbit
Jonathan Washington, Swarthmore College
Nathaniel Oco, National University (Philippines)
Tommi A Pirinen, UiT The Arctic University of Norway, Tromsø
Valentin Malykh, Huawei Noah’s Ark lab and Kazan Federal University
Varvara Logacheva, Skolkovo Institute of Science and Technology
Xiaobing Zhao, Minzu University of China
PROGRAM COMMITTEE (LISTED ALPHABETICALLY)
Alberto Poncelas, Rakuten, Singapore
Alina Karakanta, Fondazione Bruno Kessler
Amirhossein Tebbifakhr, Fondazione Bruno Kessler
Anna Currey, Amazon Web Services
Aswarth Abhilash Dara, Amazon
Arturo Oncevay, University of Edinburgh
Atul Kr. Ojha, DSI, National University of Ireland Galway & Panlingua
Language Processing LLP
Bharathi Raja Chakravarthi, DSI, National University of Ireland Galway
Beatrice Savold, University of Trento
Bogdan Babych, Heidelberg University
Chao-Hong Liu, Potamu Research Ltd
Duygu Ataman, University of Zurich
Ekaterina Vylomova, University of Melbourne, Australia
Eleni Metheniti, CLLE-CNRS and IRIT-CNRS
Francis Tyers, Indiana University
Kalika Bali, MSRI Bangalore, India
Koel Dutta Chowdhury, Saarland University (Germany)
Jade Abbott, Retro Rabbit
Jasper Kyle Catapang, University of the Philippines
John P. McCrae, DSI, National University of Ireland Galway
Liangyou Li, Noah’s Ark Lab, Huawei Technologies
Maria Art Antonette Clariño, University of the Philippines Los Baños
Mathias Müller, University of Zurich
Nathaniel Oco, National University (Philippines)
Rico Sennrich, University of Zurich
Sangjee Dondrub, Qinghai Normal University
Santanu Pal, WIPRO AI
Sardana Ivanova, University of Helsinki
Shantipriya Parida, Silo AI
Sina Ahmadi, DSI, National University of Ireland Galway
Sunit Bhattacharya, Charles University
Surafel Melaku Lakew, Amazon AI
Tommi A Pirinen, UiT The Arctic University of Norway, Tromsø
Valentin Malykh, Huawei Noah’s Ark lab and Kazan Federal University
CONTACT
Please email loresmt(a)googlegroups.com if you have any
questions/comments/suggestions.
Thanks,
Atul
The 2022 SIGNLL Conference on Computational Natural Language Learning
(CoNLL 2022, Co-located with EMNLP 2022)
Website: https://conll.org/
SIGNLL invites submissions to the 26th Conference on Computational Natural Language Learning (CoNLL 2022). The focus of CoNLL is on theoretically, cognitively and scientifically motivated approaches to computational linguistics, rather than on work driven by particular engineering applications.
Such approaches include:
- Computational learning theory and other techniques for theoretical analysis of machine learning models for NLP
- Models of first, second and bilingual language acquisition by humans
- Models of language evolution and change
- Computational simulation and analysis of findings from psycholinguistic and neurolinguistic experiments
- Analysis and interpretation of NLP models, using methods inspired by cognitive science or linguistics or other methods
- Data resources, techniques and tools for scientifically-oriented research in computational linguistics
- Connections between computational models and formal languages or linguistic theories
- Linguistic typology, translation, and other multilingual work
- Theoretically, cognitively and scientifically motivated approaches to text generation
We welcome work targeting any aspect of language, including:
- Speech and phonology
- Syntax and morphology
- Lexical, compositional and discourse semantics
- Dialogue and interactive language use
- Sociolinguistics
- Multimodal and grounded language learning
We do not restrict the topic of submissions to fall into this list. However, the submissions’ relevance to the conference’s focus on theoretically, cognitively and scientifically motivated approaches will play an important role in the review process.
Submitted papers must be anonymous and use the EMNLP 2022 template. Submitted papers may consist of up to 8 pages of content plus unlimited space for references. Authors of accepted papers will have an additional page to address reviewers’ comments in the camera-ready version (9 pages of content in total, excluding references). Optional anonymized supplementary materials and a PDF appendix are allowed, according to the EMNLP 2022 guidelines. Please refer to the EMNLP 2022 Call for Papers for more details on the submission format. Submission is electronic, using the Softconf START conference management system.
CoNLL adheres to the ACL anonymity policy, as described in the EMNLP 2022 Call for Papers. Briefly, non-anonymized manuscripts submitted to CoNLL cannot be posted to preprint websites such as arXiv or advertised on social media after May 30th, 2022.
Multiple submission policy
CoNLL 2022 will not accept papers that are currently under submission, or that will be submitted to other meetings or publications, including EMNLP. Papers submitted elsewhere as well as papers that overlap significantly in content or results with papers that will be (or have been) published elsewhere will be rejected. Authors submitting more than one paper to CoNLL 2022 must ensure that the submissions do not overlap significantly (>25%) with each other in content or results.
CoNLL 2022 has the same policy as EMNLP 2022 regarding ARR submissions. This means that CoNLL 2022 will also accept submissions of ARR-reviewed papers, provided that the ARR reviews and meta-reviews are available by the ARR commitment deadline. We follow the EMNLP policy for papers that were previously submitted to ARR, or significantly overlap (>25%) with such submissions.
Important Dates
Anonymity period begins: May 30th, 2022
Submission deadline for START direct submissions: Thursday June 30th, 2022
Commitment deadline for ARR papers: August 1st, 2022
Notification of acceptance: Mid-September, 2022
Camera ready papers due: October 15th, 2022
Conference: December 7th, 8th, 2022
All deadlines are at 11:59pm UTC-12h ("anywhere on earth").
The independent research group Trustworthy Human Language Technologies (TrustHLT) at the Department of Computer Science of the Technical University of Darmstadt, Germany has a job opening for a
Postdoctoral researcher (m/f/d)
in the recently acquired project “PrivaLingo: Truly Privacy-Preserving Machine Translation” by Dr. Ivan Habernal.
This position will focus on a broad range of research questions related to privacy-preserving NLP models with a special focus on neural machine translation. A solid background in machine learning for natural language processing is essential, prior experience with differential privacy in model training is a plus. Wages and salaries are based on the collective agreement applicable to the TU Darmstadt (TV-TU Darmstadt). The starting date is as soon as possible, the position is funded until April 2024.
Candidates
The ideal candidate hold a PhD degree in computer science, computational linguistics, machine learning, or a related discipline, has a strong interest in privacy in natural language processing, excellent analytical and programming skills, is a team player, and is fluent in English.
Diversity
TU Darmstadt is strongly committed to diversity and particularly welcomes applications from members of underrepresented groups. Applications from female candidates are highly encouraged.
Team
TrustHLT is an independent research group led by Dr. Ivan Habernal, appointed at the Department of Computer Science of the Technical University of Darmstadt. The group conducts research in the field of natural language processing with a focus on privacy-preserving technologies and legal argumentation, see www.trusthlt.org for more details. The Department of Computer Science at TU Darmstadt regularly ranks among the top in Germany.
Application
Please send your detailed CV including a publication list, names of two referees, and a letter of motivation outlining your research interests to ivan.habernal(a)tu-darmstadt.de, subject: “Postdoc application PrivaLingo”. Send all documents as a single PDF (“PDF Arranger” is a helpful tool, for instance). Please do not hesitate to contact Dr. Habernal should you have any further questions. Deadline for applications is June 30, 2022. Applications arriving after the deadline will still be considered if the position is not filled yet.