Workshop on Multilingual Surface Realization
Melbourne, July 19th 2018
The first workshop on multilingual surface realization aims at bringing together people who are interested in surface-oriented Natural Language Generation problems such as word order determination, inflection, functional word determination, paraphrasing, etc. It will accomodate for the presentation of the results of the Surface Realization Shared Task 2018 and of a number of technichal papers on the topic.
The workshop will be held at ACL'18 in Melbourne, Australia, on July 19th 2018.
Call for papers↑
Natural Language Generation (NLG) is in the ascendant both as a stand-alone data-to-text or text-to-text task and as part of downstream applications (see, e.g., abstractive summarization, dialogue-based interaction, question answering, etc.).
Only in 2017, three “deep” NLG shared tasks that focused on language generation from
abstract semantic representations have been organized (although for English only):
WebNLG, SemEval Task 9
However, when compared to, e.g., parsing or
machine translation, NLG still lags behind in terms of theoretical advances. Thus, while recent years witnessed a shift of the processing paradigm in these areas from traditional supervised machine learning techniques to deep learning techniques, NLG did not arrive there fully yet.
Similarly, NLG still does not make full use of the available resources in the way, e.g., parsing does. For instance, the multilingual Universal Dependencies (UD) dataset has already been used for the CoNLL'17 parsing shared task. This dataset, which currently consists of 102 treebanks covering about 60 languages and can be downloaded freely, facilitates the development of large scale applications that work potentially across all of the UD treebank languages in a uniform fashion.
MSR-WS aims to change the situation and put NLG, and, in particular, surface generation, onto the main stream research agenda of Computational Linguistics, bringing together communities that hardly collaborated so far. It will provide a forum for the presentation of the results of the currently open multilingual Surface Realization Shared Task 2018 (SR’18) and of high quality papers on surface realization and related topics. SR’18 focuses on multilingual surface generation starting from UD treebanks. Since UDs are structures with a degree of abstraction that is targeted by state-of- the-art parsing, such that that the challenge to reverse neural network parsing algorithms for generation becomes a plausible research question, SR’18 solicits, apart from genuine generation approaches, contributions by the parsing community. SR’18 also aims to attract participants from other areas such as Computer Assisted Language Learning (and, in particular, grammatical error correction, since one of the tracks of the SR’18 is the generation of functional words such as bound prepositions and auxiliaries, whose correct introduction/omission is one of the primary challenges for language learners).
To complement the presentation of the SR’18 results, MSR-WS solicits contributions on all topics that are related to surface realization in NLG. Sought are presentations of cutting edge approaches that address problems of surface-oriented generation such as grammatical and/or information structure-driven word order determination, inflection, functional word determination, paraphrasing, etc. The presented works are expected to be a clear contribution to the progress in robust multilingual surface generation, i.e., be language-independent or easily portable from one language to another and clearly scalable. The topics of interest include, but are not limited to:
- Linearization in NLG
- Multilingual approaches to surface realization
- Function word generation
- Inflection in NLG
- Joint generation from abstract representations
- Surface-oriented text simplification
- Surface-oriented spoken language generation
- Application of surface realization for grammatical error correction
- NLG in surface-oriented paraphrasing
- Deep learning approaches to NLG
Shared Task (endorsed by SIGGEN)↑
Details for the Shared Task can be found on the Task Page.
Important Dates↑ 09/04: The submission deadline has been extended!
Dec 11, 2017 : First call for Workshop papers
Mar 8, 2017 : Second call for Workshop papers
May 7, 2018 : Notification of acceptance
May 28, 2018 : Camera-ready papers due
Jul 19, 2018 : Workshop date
Submissions↑ We invite full papers (8 pages) and short papers (4 pages); long and short papers have unlimited references.
To encourage inclusiveness and the presentation of speculative and recent work, inclusion in the conference proceedings will be made optional. The author’s preference should be indicated with the final submission.
Submissions must conform the official style guidelines, and be in PDF format, using the Softconf START conference management system.
Please refer to the ACL conference website for new policies for submission, review, and citation, and official style guidelines.
For registration information, please visit https://acl2018.org/registration/
Programme↑ The workshop will consist of technical presentations, a poster session with WS papers and ST systems, the presentation of the shared task results, a round table and an invited talk. The final schedule is provided below.
|9:00|| Invited Talk: Hadar Shemtov
Challenges in Natural Language Generation in Conversational Interfaces: How to Build a Scalable and Reliable Eloquent Assistant
|10:00|| Oral presentation
The First Multilingual Surface Realisation Shared Task: Overview and Evaluation Results
Simon Mille, Anja Belz, Bernd Bohnet, Yvette Graham, Emily Pitler and Leo Wanner
|11:00|| Oral presentations
BinLin: A Simple Method of Dependency Tree Linearization
Yevgeniy Puzikov and Iryna Gurevych
IIT (BHU) Varanasi at MSR-SRST 2018: A Language Model Based Approach for Natural Language Generation
Shreyansh Singh, Ayush Sharma, Avi Chawla and A.K. Singh
Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach
Thiago Castro Ferreira, Sander Wubben and Emiel Krahmer
|13:45|| Oral presentation
The OSU Realizer for SRST '18: Neural Sequence-to-Sequence Inflection and Incremental Locality-Based Linearization
David King and Michael White
|14:15|| Poster Session
Generating High-Quality Surface Realizations Using Data Augmentation and Factored Sequence Models
Henry Elder and Chris Hokamp
AX Semantics' Submission to the Surface Realization Shared Task 2018
Andreas Madsack, Johanna Heininger, Nyamsuren Davaasambuu, Vitaliia Voronik, Michael Käufl and Robert Weißgraeber
NILC-SWORNEMO at the Surface Realization Shared Task: Exploring Syntax-Based Word Ordering using Neural Models
Marco Antonio Sobrevilla Cabezudo and Thiago Pardo
The DipInfo-UniTo system for SRST 2018
Valerio Basile and Alessandro Mazzei
Invited talk: Hadar Shemtov – Generation and Dialog Specialist at Google, Head of NLG, dialog and summarization groups at Google
Miguel Ballesteros, IBM Research, USA
Anders Björkelund, University of Stuttgart, Germany
Johan Bos, University of Groningen, Netherlands
Robert Dale, Macquarie University, Australia
Katja Filippova, Google Research, Switzerland
Claire Gardent, CNRS, LORIA, France
Kim Gerdes, Sorbonne Nouvelle, France
Yannis Konstas, Heriot Watt University, UK
Emiel Krahmer, Tilburg University, Netherlands
Mirella Lapata, University of Edinburgh, UK
Jonathan May, Information Sciences Institute, USA
David McDonald, Sift Inc., USA
Ryan McDonald, Google Research, USA
Detmar Meurers, University of Tübingen, Germany
Alexis Nasr, University of Aix Marseille, France
Joakim Nivre, Uppsala University, Sweden
Stephan Oepen, University of Oslo, Norway
Horacio Saggion, Pompeu Fabra University, Spain
Lucia Specia, University of Sheffield, UK
Kees Van Deemter, University of Aberdeen, UK
Sina Zarrieß, University of Bielefeld, Germany
Yue Zhang, Singapore University of Technology and Design, Singapore
|Simon Mille|| TALN
Pompeu Fabra University,
|Bernd Bohnet|| Google Research,
Pompeu Fabra University and ICREA,
|Anya Belz|| University of Brighton
|Emily Pitler|| Google Research,
New-York, NY, USA
Please send us an email at email@example.com if you have any question.