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MMTLRL 2021 : First Workshop on Multimodal Machine Translation for Low Resource Languages


When Sep 7, 2021 - Sep 7, 2021
Where online
Submission Deadline Jul 23, 2021
Notification Due Aug 15, 2021
Final Version Due Aug 31, 2021
Categories    NLP

Call For Papers

Call For Papers:: MMTLRL-2021@RANLP-2021

First Workshop on Multimodal Machine Translation for Low Resource Languages (MMTLRL-2021)

Language does not exist in a vacuum. Yet, for a long time, large parts of NLP have focused on text- (or speech-) only scenarios: most work on machine translation (MT) e.g. is on text-to-text MT. In principle, the inclusion of additional context in the form of other modalities offers the promise of improving a translation. In practice, this is often hard (Lala et al. 2017, Elliott 2018). In this workshop, we would like to combine two strands of research that are hitherto not well connected: research on low-resource MT and research on multi-modal MT (MMMT). While there has been important progress on both sides, including unsupervised (Artetxe et al. 2018, Lample et al. 2018) and self-supervised MT (Ruiter et al. 2019); and neural-network-based modality combinations in MMMT (Çağlayan et al. 2019), the potential of mustering information in other modalities (such as images, videos and spoken language) to complement the text signal in low-resource MT has not yet been explored extensively. However, a combination may hold promise: a richer multimodal signal may help address some of the challenges that come with low-resource scenarios. Of course, there are no guarantees: a richer multimodal signal and with it an increase in the dimensionality of the data may make the problem worse.


We invite original contributions describing the latest trends, developments and solutions. Topics of interest include, but are not limited to:

Data harvesting and preparation for low resource MMMT

Multimodality and its impact on machine translation

MMMT for low resource scenarios

Neural approaches towards multimodal machine translations

Speech and Visual modalities for MMMT

Multimodal quality estimation

Multilingual MMMT

Multimodal attention

Evaluation of MMMT


All papers must be submitted in PDF format through the conference management system at The papers should follow the format of the main conference, described at the main RANLP website, Submission Guidelines Section.

Full Papers must describe original unpublished work in any topic area of the workshop.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.


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 e-mail.


Workshop paper submission deadline: 30 June 2021

Workshop paper acceptance notification: 31 July 2021

Workshop paper camera-ready versions: 31 August 2021

Workshop video presentations due: 31 August 2021

Workshop camera-ready proceedings ready: 5 September 2021

Workshops: 7 September 2021


Lucia Specia, Imperial College London, England
Marine Carpuat, University of Maryland, USA


Thoudam Doren Singh, NIT Silchar, India
Cristina España-Bonet, DFKI, Germany
Sivaji Bandyopadhyay, NIT Silchar, India
Josef Van Genabith, DFKI and Universität des Saarlandes, Germany

(Alphabetically ordered on last name)

David Ifeoluwa Adelani, Universität des Saarlandes, Germany
Loïc Barrault, University of Sheffield
Pushpak Bhattacharyya, IIT Bombay, India
Koel Dutta Chowdhury, Universität des Saarlandes, Germany
Marta R. Costa-jussà, Universitat Politècnica de Catalunya, Spain
Alexander Fraser, LMU Munich, Germany
Julia Kreutzer, Google
Gorka Labaka, University of the Basque Country (UPV/EHU), Spain
Pranava Madhyastha, Imperial College London, England
Vukosi Marivate, University of Pretoria, South Africa
Loitongbam Sanayai Meetei, National Institute of Technology Silchar, India
Preslav Nakov, Qatar Computing Research Institute, HBKU
Shantipriya Parida, Idiap Research Institute, Switzerland
Alok Singh, National Institute of Technology Silchar, India
Salam Michael Singh, National Institute of Technology Silchar, India
Xabier Soto, University of the Basque Country (UPV/EHU), Spain
Jörg Tiedeman, University of Helsinki, Finland
Deyi Xiong, Tianjin University, China
Jingyi Zhang, DFKI, Germany

To contact the organizers, you can email at:

MMTLRL-2021 Website:

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