*Call For Papers*
*LREC 2018 Industry Track will take place on 10 May, 2018*
http://lrec2018.lrec-conf.org/en/industry-track/
The European Language Resource Association (ELRA, www.elra.info) is glad
to announce the 11th edition of LREC, organised with the support of
international organisations – many from Asia: the Asian Federation of
Natural Language Processing (AFNLP), Oriental COCOSDA, the Association
of Natural Language Processing - Japan, the Chinese Information
Processing Society of China, the Linguistic Data Consortium, the
Artificial Intelligence Association of Thailand, the Korean Society for
Language and Information, the Korean Special Interest Group of Human and
Cognitive Language Technology, and a number of industrial partners and
supporters.
Since the first LREC held in Granada in 1998, LREC has become the major
event on Language Resources (LRs) and Evaluation for Language
Technologies (LT) with over 1200 attendees from all over the world. LREC
provides a unique forum for researchers, industrials and funding
agencies from across a wide spectrum of areas to discuss problems and
opportunities, find new synergies and promote initiatives for
international cooperation, in support to investigations in language
sciences, progress and innovation in language technologies and
development of corresponding products, services and applications, and
standards. As a hot LREC 2018 topic, an industry track will take place
during the main conference.
*Track Description*
Human language technologies have become increasingly important parts of
our lives. These technologies have emerged from decades of
collaborations between academic and industrial research organizations;
collaborations are made possible by the unique strengths of both
communities and a set of shared practices (algorithms, evaluation
methods, datasets, and the like). But despite this, there are
substantial differences between research in academic and industrial
settings.
In contrast to academic research: industrial speech and language
technologies may pose unique challenges of scale; language resources
from industry may demand different algorithms or evaluation
methodologies than in academic settings; and the practices of academic
and industrial settings may converge on distinct methods for the same
problem; industrial systems and practices may pose ethical challenges
not present in academic settings.
*Topics of Interest*
Topics include but not limited to:
/*Industrial systems*/
For this topic we welcome submissions which discuss industrial systems.
They may describe technical innovations which are enabled by the
industrial setting, or they may describe the implementation of a
deployed industrial system. We also welcome submissions which discuss
failures to replicate "state-of-the-art" performance when provided with
the affordances of an industrial setting. Finally, we also welcome
opinion papers which discuss similarities and differences between
academic and industrial practices for system development and evaluation,
or which consider ethical issues specific to systems deployed at
industry scale.
/*Tools and platforms for data collection*/
Data collected in an industry setting may pose specific technical,
legal, and ethical challenges not normally encountered in academic
settings. The infrastructure within which developers in industry operate
can provide tremendous advantages, but also unique challenges. There can
be significant differences in the context of a tool's operator or a data
platform's customer in industry vs. academic applications. Platforms may
be globally distributed, and the scale itself of the data and of the
deployment of industry technologies can add significant complexity,
which may demand innovative approaches. Industry developers may also
face special problems in defining users, their orientation to their
tasks, and what constitutes a successful interaction from the standpoint
of the user and of data acquisition efforts. We welcome submissions
which discuss industrial tools and platforms used to collect data.
/*Human computation in industry*/
Industrial language technologies depend on machine learning methods,
which in turn require large, diverse collections of labeled data
collected from humans for rapid iterative development and refinement. We
welcome submissions which discuss issues in experimental design for
human computation, the challenges of quality, diversity, and
representation in crowdsourcing, and ethical issues posed by data
collection via crowdsourcing and outsourcing.
/* Asian languages*/
One goal for this year's LREC is to strengthen connections with the
Asian speech and language community. Therefore we welcome submissions
which discuss industrial resources and technologies specific to the
challenges posed by Asian languages.
/*Spoken languages and dialects*/
We are particularly interested in work which describes industrial
resources and technologies for spoken languages, non-standard dialects,
and therefore we welcome submissions which focus on these topics,
especially those submissions which contrast spoken and written
language—or standard and non-standard language—resources and technologies.
/*Less-resourced languages*/
One special topic for this year's LREC is less-resourced languages,
especially those used in Asia, and therefore we welcome submissions
which discuss resources and technologies for such languages in an
industry setting.
*Submission*
We encourage submissions of papers for oral or poster presentation.
Papers should follow theLREC stylesheet. The working language of the
track is English. Submitted papers must be written and delivered in
English and be up to 4 pages in length.
*Submission page: https://www.softconf.com/lrec2018/IndustryTrack/. *
*Identify, Describe and Share your LRs!*
Describing your language resources (LRs) in the LRE Map is now a normal
practice in the submission procedure of LREC (introduced in 2010 and
adopted by other conferences). This LREC feature is available to
submissions within this track and highly recommended.
To continue the efforts initiated at LREC 2014 about “Sharing LRs”
(data, tools, web-services, etc.), authors will have the possibility,
when submitting a paper, to upload LRs in a special LREC repository.
This effort of sharing LRs, linked to the LRE Map for their description,
may become a new “regular” feature for conferences in our field, thus
contributing to creating a common repository where everyone can deposit
and share data.
As scientific work requires accurate citations of referenced work so as
to allow the community to understand the whole context and also
replicate the experiments conducted by other researchers, LREC 2018
endorses the need to uniquely Identify LRs through the use of the
International Standard Language Resource Number (ISLRN, www.islrn.org),
a Persistent Unique Identifier to be assigned to each LR. The assignment
of ISLRNs to LRs cited in LREC papers will be offered at submission time.
*Important Dates & Deadlines*
* Paper submission: 10 February 2018
* Notification of acceptance: 12 March 2018
* Camera-ready paper: 26 March 2018
* Track Date: 10 May 2018
*Organizing Committee*
* Linne Ha, Director of Research Program in NLU, Research & Machine
Intelligence, Google (New York)
* Kyle Gorman, Software Engineer, Speech & Language Algorithms,
Research & Machine Intelligence, Google (New York)
* Jimmy Kunzmann, Manager Research and Development, European Media
Laboratory GmBH (EML), (Heidelberg)
* Constantine Lignos, Computer Scientist, Information Sciences
Institute, University of Southern California
* Richard Sproat, Senior Research Scientist, Speech & Language
Algorithms, Research & Machine Intelligence, Google (New York)
* Martin Jansche, Software Engineer, NLU, Research & Machine
Intelligence, Google (London)
* Ryan MacDonald, Research Scientist, NLU, Research & Machine
Intelligence, Google (London)
* Tomoki Nagase, Senior Researcher, Artificial Intelligence Lab.,
Fujitsu Laboratories (Tokyo)
* Khalid Choukri, ELDA CEO (Paris)
*Industry Track Contact*
Send your inquiries to: *[email protected]
<mailto:[email protected]>*
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*LREC 2018 General Information*
[email protected]
www.lrec-conf.org/lrec2018
Follow us on Twitter: @LREC2018
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