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MMTLRL 2021 : First Workshop on Multimodal Machine Translation for Low Resource Languages | |||||||||||||||
Link: https://sites.google.com/view/mmtlrl-2021/home | |||||||||||||||
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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. CALL FOR PAPERS 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 SUBMISSION GUIDELINES All papers must be submitted in PDF format through the conference management system at https://www.softconf.com/ranlp2021/MMTLRL2021/. 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. DOUBLE SUBMISSION 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. IMPORTANT DATES 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 KEYNOTE SPEAKERS Lucia Specia, Imperial College London, England Marine Carpuat, University of Maryland, USA ORGANIZERS 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 TECHNICAL PROGRAMME COMMITTEE (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: mmtlrl2021@gmail.com MMTLRL-2021 Website: https://sites.google.com/view/mmtlrl-2021/home |
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