!!!!!!!!!! The deadline for submission has been extended to July 20th !!!!!!!!!! Upload Submissions Now https://cmt3.research.microsoft.com/AMTA2022

The First Workshop on Corpus Generation and Corpus Augmentation for Machine Translation (CoCo4MT) https://sites.google.com/view/coco4mt @ AMTA – 2022 This 15th biennial conference of the Association for Machine Translation in the Americas 12-16 September 2022, Orlando, Florida, USA

INVITED TALKS

Jörg Tiedemann University of Helsinki Julia Kreutzer Google Research Maria Nadejde Amazon

SCOPE

It is a well-known fact that machine translation systems, especially those that use deep learning, require massive amounts of data. Several resources for languages are not available in their human-created format. Some of the types of resources available are monolingual, multilingual, translation memories, and lexicons. Those types of resources are generally created for formal purposes such as parliamentary collections when parallel and more informal situations when monolingual. The quality and abundance of resources including corpora used for formal reasons is generally higher than those used for informal purposes. Additionally, corpora for low-resource languages, languages with less digital resources available, tends to be less abundant and of lower quality.

CoCo4MT sets out to be the first workshop centered around research that focuses on corpora creation, cleansing, and augmentation techniques specifically for machine translation. We accept work that covers any spoken language (including high-resource languages) but we are specifically interested in those submissions that are on languages with limited existing resources (low-resource languages) where resources are not highly available.

The goal of this workshop is to begin to close the gap between corpora available for low-resource translation systems and promote high-quality data for online systems that can be used by native speakers of low-resource languages is of particular interest. Therefore, It will be beneficial if the techniques presented in research papers include their impact on the quality of MT output and how they can be used in the real world.

CoCo4MT aims to encourage research on new and undiscovered techniques. We hope that submissions will provide high-quality corpora that is available publicly for download and can be used to increase machine translation performance thus encouraging new dataset creation for multiple languages that will, in turn, provide a general workshop to consult for corpora needs in the future. The workshop’s success will be measured by the following key performance indicators:

- Promotes the ongoing increase in quality of machine translation systems when measured by standard measurements, - Provides a meeting place for collaboration from several research areas to increase the availability of commonly used corpora and new corpora, - Drives innovation to address the need for higher quality and abundance of low-resource language data.

TOPICS

We are highly interested in original research papers on the topics below; however, we welcome all novel ideas that cover research on corpora techniques.

- Difficulties with using existing corpora (e.g., political considerations or domain limitations) and their effects on final MT systems, - Strategies for collecting new MT datasets (e.g., via crowdsourcing), - Data augmentation techniques, - Data cleansing and denoising techniques, - Quality control strategies for MT data, - Exploration of datasets for pretraining or auxiliary tasks for training MT systems.

SUBMISSION INFORMATION

There is one type of submission in the workshop: Research, review and position paper. The length of each paper should be at least four (4) and not exceed ten (10) pages, plus unlimited pages for references. Submissions should be formatted according to the official AMTA 2022 style templates (PDF, LaTeX, Word). Accepted papers will be published on-line in the AMTA 2022 proceedings which includes the ACL Anthology and will be presented at the conference either orally or as a poster.

Submissions must be anonymized and should be done using the official conference management system (https://cmt3.research.microsoft.com/AMTA2022). Scientific papers that have been or will be submitted to other venues must be declared as such, and must be withdrawn from the other venues if accepted and published at CoCo4MT. The review will be double-blind.

We would like to encourage authors to cite papers written in ANY language that are related to the topics, as long as both original bibliographic items and their corresponding English translations are provided.

Registration will be handled by the main conference. (To be announced)

IMPORTANT DATES

June 1, 2022 – Call for papers released June 15, 2022 – Second call for papers June 29, 2022 – Third and final call for papers July 20, 2022 – Paper submissions due (updated extension!) July 27, 2022 – Notification of acceptance August 7, 2022 – Camera-ready due August 31, 2022 – Video recordings due September 16, 2022 - CoCo4MT workshop

CONTACT

CoCo4MT Workshop Organizers coco4mt2022@googlegroups.com

ORGANIZING COMMITTEE (listed alphabetically)

Constantine Lignos Brandeis University John E. Ortega New York University and University of Santiago de Compostela (CITIUS) Katharina Kann University of Colorado Boulder Maja Popopvić ADAPT Centre at Dublin City University Marine Carpuat University of Maryland Shabnam Tafreshi University of Maryland William Chen Carnegie Mellon University

PROGRAM COMMITTEE (listed alphabetically tentative)

Abteen Ebrahimi University of Colorado Boulder Adelani David Saarland University Ananya Ganesh University of Colorado Boulder Alberto Poncelas ADAPT Centre at Dublin City University Amirhossein Tebbifakhr University of Trento Anna Currey Amazon Arturo Oncevay University of Edinburgh Atul Kr. Ojha National University of Ireland Galway Bharathi Raja Chakravarthi National University of Ireland Galway Beatrice Savoldi University of Trento Bogdan Babych Heidelberg University Briakou Eleftheria University of Maryland Dossou Bonaventure Mila Quebec AI Institute Duygu Ataman New York University Eleni Metheniti Université Toulosse - Paul Sabatier Francis Tyers Indiana University Jasper Kyle Catapang University of Birmingham John E. Ortega New York University and USC - CITIUS José Ramom Pichel Campos Universidade de Santiago de Compostela - CITIUS Kalika Bali Microsoft Koel Dutta Chowdhury Saarland University Liangyou Li Huawei Manuel Mager University of Stuttgart Maria Art Antonette Clariño University of the Philippines Los Baños Mathias Müller University of Zurich Nathaniel Oco De La Salle University Niu Xing Amazon Pablo Gamallo Universidade de Santiago de Compostela - CITIUS Rodolfo Joel Zevallos Salazar Universitat Pompeu Fabra Rico Sennrich University of Zurich Sangjee Dondrub Qinghai Normal University Santanu Pal Saarland University Sardana Ivanova University of Helsinki Shantipriya Parida Silo AI Surafel Melaku Lakew Amazon Tommi A Pirinen University of Tromsø Valentin Malykh Moscow Institute of Physics and Technology