Details of Grant 

EPSRC Reference:	EP/I032320/1
Title:	Generation Challenges 2011: Towards a Surface Realisation Shared Task
Principal Investigator:	Belz, Professor A
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:	Sch of Computing, Engineering & Maths
Organisation:	University of Brighton
Scheme:	Standard Research
Starts:	01 May 2011	Ends:	30 April 2012	Value (£):	67,890
EPSRC Research Topic Classifications:	Artificial Intelligence Comput./Corpus Linguistics Human Communication in ICT
EPSRC Industrial Sector Classifications:	No relevance to Underpinning Sectors
Related Grants:
Panel History:	Panel Date Panel Name Outcome 01 Feb 2011 EPSRC ICT Responsive Mode - Feb 2011 Announced
Summary on Grant Application Form
Computers can now perform some writing tasks well (e.g. transcription and spell checking), but we still lack goodcomputational solutions for writing tasks which involve the creation of new text (as opposed to the typing orchecking of existing text). Natural language generation (NLG) is the branch of computer science that aims toaddress this lack, by developing methods and tools for the computational generation of spoken and writtenlanguage. NLG technology has a vast range of potential applications, including increasing the efficiency oftext-production processes (e.g. automated letter and report writing) and making information available in verbal formthat would otherwise be inaccessible (e.g. to the blind) or more time-consuming to process (e.g. converting weatherdata to a textual summary). However, NLG is only just beginning to fulfil this potential. Among the reasons is thefact that NLG did not until recently employ comparative forms of evaluation, as are essential for effectivecomparison of alternative approaches, consolidation and collective scientific progress.The NLG field's evaluation tradition lies in user-oriented and task-based evaluation of complete systems.This tradition is very different from the comparative evaluation paradigms that are predominant in otherareas of Natural Language Processing (NLP) where shared data resources, intrinsic, automatically computedmetrics, and human ratings of quality provide time-efficient and low-cost ways of comparing new systems andtechniques against existing approaches. In contrast, in NLG, until a few years ago, there simply was no comparative evaluation of independently developed alternative approaches. Yet without comparative evaluation there can be noconsolidation or collective progress in a field of research, and individual researchers and groups are left toprogress more or less separately. The GenChal initiative has firmly established comparative evaluation in NLG andproduced data sets and software tools to support it. Past shared tasks have addressed the subfield of referencegeneration and specific applications, and the time is now right to tackle a more ambitious challenge.With the Surface Realisation Task that forms the core of the present proposal, we are aiming for something trulygroundbreaking and of great potential use in practical applications: the development of a new generation of surfacerealisers that can be directly compared and, because they work from common input, can be substituted for eachother. Ultimately, this will mean that data-to-text generation, MT, summarisation and dialogue systems (amongother fields) will directly benefit from the availability of a range of reusable realisation components which systembuilders can test to determine which is best for their purpose, something that has not been possible before.
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Organisation Website:	http://www.bton.ac.uk