THE FOURTH WORKSHOP ON TECHNOLOGIES FOR MT OF LOW-RESOURCE LANGUAGES (LoResMT 2021)

LoResMT 2021


Computational Linguistics



THE FOURTH WORKSHOP ON TECHNOLOGIES FOR MT OF LOW-RESOURCE LANGUAGES
(LoResMT 2021)
https://sites.google.com/view/loresmt/
@ MT Summit XVIII – 2021
The 18th biennial conference of the International Association of Machine
Translation
16-20 August 2021, Orlando, Florida, USA
INVITED TALKS
1. Mathias Müller
Institut für Computerlinguistik, Universität Zürich
“On Meaningful Evaluation of Machine Translation Systems”
2. To be announced
SCOPE
Based on the success of past low-resource machine translation (MT)
workshops at AACL-IJCNLP 2020 (http://aacl2020.org/), MT Summit 2019
(https://www.mtsummit2019.com) and AMTA 2018 (https://amtaweb.org/), we
introduce the fourth LoResMT workshop at MT Summit 2021.
Like its predecessors, this workshop will bring together researchers and
translators of low-resource languages to compare and contrast how each
use digital technology for translation.
Specifically, the workshop focuses on novel advances on the coverage of
even more languages than past workshops with different geographical
presence, degree of diffusion and digitalization.
We solicit original work on low-resource translation which includes, but
is not limited to, MT systems that include word
tokenizers/de-tokenizers, word segmenters, morphological analyzers, and
more.
We furthermore invite work that includes MT systems based on neural
networks along with their methods, natural language processing
approaches, and overall coverage of low-resource languages.
Additionally, novel work covering translations of COVID-related text and
their practical use for low-resource communities are of high interest.
The goal of this workshop is to begin to close the gap between
low-resource translation systems and their practical use in the real
world.
Online systems and original research that can be used by native speakers
of low-resource languages is of particular interest.
Therefore, It will be beneficial if the evaluations of these tools in
research papers include their impact on the quality of MT output and how
they can be used in the real world.
We are also happy to announce the introduction of a new shared task
focused on the construction of machine translation systems for
COVID-related texts.
The task aims to encourage research on machine translation systems
involving three low-resource language groups: (1) a sign language, (2) a
language from the Americas and (3) a language from India. More
information will be announced soon!
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
There are two types of submissions in the workshop.
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 MT Summit 2021
style templates (PDF, LaTeX, Word). Accepted papers will be published
on-line in the MT Summit 2021 proceedings and will be presented at the
conference either orally or as a poster.
Submissions must be anonymized and should be done using the official
conference management system
(https://cmt3.research.microsoft.com/MTSUMMIT2021).
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 will be handled by the main conference. (To be announced)
IMPORTANT DATES
March 25, 2021 – Call for papers released
April 22, 2021 – Second call for papers
May 20, 2021 – Third call for papers
June 17 , 2021 – Paper submissions due
July 8 , 2021 – Notification of acceptance
July 15, 2021 – Camera-ready due
August 5, 2021 – Video recordings due
August 16, 2021 - LoResMT workshop
CONTACT
LoResMT 2021 Workshop Chair:
John Ortega (jortega@cs.nyu.edu)
Shared Task Chairs:
Atul Kr. Ojha (atulkumar.ojha@insight-centre.org)
Katharina Kann (katharina.kann@colorado.edu)
Chao-Hong Liu (ch.liu@acm.org)
ORGANIZING COMMITTEE (listed alphabetically)
Atul Kr. Ojha DSI, National University of Ireland Galway & Panlingua
Language Processing LLP
Chao-Hong Liu Potamu Research Ltd
Jade Abbott Retro Rabbit
John Ortega New York University
Jonathan Washington Swarthmore College
Katharina Kann University of Colorado at Boulder
Nathaniel Oco National University (Philippines)
Surafel Melaku Lakew Amazon AI
Tommi A Pirinen University of Hamburg
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