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LINGUIST List 21.28

Tue Jan 05 2010

Calls: Computational Ling, Cognitive Science, Neuroling/USA

Editor for this issue: Kate Wu <katelinguistlist.org>


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        1.    Brian Murphy, NAACL 2010 Workshop on Computational Neurolinguistics

Message 1: NAACL 2010 Workshop on Computational Neurolinguistics
Date: 22-Dec-2009
From: Brian Murphy <brian.murphyunitn.it>
Subject: NAACL 2010 Workshop on Computational Neurolinguistics
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Full Title: NAACL 2010 Workshop on Computational Neurolinguistics

Date: 05-Jun-2010 - 06-Jun-2010
Location: Los Angeles, California, USA
Contact Person: Brian Murphy
Meeting Email: brian.murphyunitn.it
Web Site: http://sites.google.com/site/compneurowsnaacl10/

Linguistic Field(s): Cognitive Science; Computational Linguistics;
Neurolinguistics; Psycholinguistics

Call Deadline: 01-Mar-2010

Meeting Description:

The first Workshop on Computational Neurolinguistics will be held at NAACL next
June in Los Angeles. Invited speakers will introduce the audience to the
fundamentals of neurolinguistics, and computational models of neural activity.

Call for Papers

Workshop on Computational Neurolinguistics, NAACL HLT 2010

The first Workshop on Computational Neurolinguistics will be held at NAACL next
June in Los Angeles. We welcome submissions on the computational treatment of
any aspect of language, that either makes use of neural recordings or of
biologically realistic neuronal models. To encourage submissions from the
broadest community, the organisers are releasing two neural activity datasets,
fMRI and EEG, described below. Submissions should be made through the NAACL
system, with a deadline of March 1st, 2010:
https://www.softconf.com/naaclhlt2010/neuroling/

Outline:
Computational neurolinguistics is an emerging research area which integrates
recent advances in computational linguistics and cognitive neuroscience, with
the objective of developing cognitively plausible models of language and gaining
a better understanding of the human language system. It builds on research in
decoding cognitive states from recordings of neural activity, and computational
models of lexical representations and sentence processing. Published work in
this area includes the discovery of semantic features in neural activity
(Mitchell et al, 2008), using brain signals for the relative evaluation of
corpus semantic models (Murphy et al, 2009), and recognizing the semantics of
adjective-noun meaning composition (Chang et al, 2009).

On-going research focuses on a number of topics such as brain-computer
interfaces to provide dictation systems for paraplegic patients, and algorithms
to perform tagging and shallow parsing of neural activity recorded during
sentence comprehension. Both computational linguistics and neuroscience stand to
gain from these techniques. In computational linguistics, the cognitive
plausibility of language models has primarily been evaluated against collections
of subjective intuitions (e.g. semantic feature norms, grammaticality judgments,
corpus annotations, dictionaries). Evaluation of the large body of Computational
Linguistics work based on data driven distributional approaches has also relied
on hand-crafted resources such as WordNet or data sets manually tagged with a
predefined list of categories. Comparison with neural data may provide a more
objective yardstick for both models and resources. And in brain imaging,
language-related research has often been limited to relatively coarse analyses
(e.g. high level features such as animacy or part-of-speech) but now
computational neurolinguistic methods have leveraged the richness of
corpus-based descriptions to extract finer-grained representations for single
lexemes.

Advances in computational neurolinguistics require close collaboration between
computational linguists and neuroscientists. To this end, an interdisciplinary
workshop can play a key role in advancing existing and initiating new research.
We hope that it will attract an interdisciplinary target audience consisting of
computational linguists, machine learning researchers, computational
neuroscientists and cognitive scientists.

Topics of Interest:
Computational Linguistic Focus
- Word-level analyses (e.g. corpus semantic models, lexica, lexical relations
and ontologies, parts-of-speech, word senses, morphology)
- Phrase-level analyses (e.g. word compounds, meaning composition in multi-word
expressions)

Machine Learning Focus
- Decoding of cognitive states from neural activity
- Feature selection and data mining techniques for decoding linguistic information

Neural Science Focus
- Brain imaging techniques: fMRI, EEG, MEG, NIRS, including cross-modality
analysis (e.g. combining fMRI and EEG)
- Localizing Regions of Interest (e.g. identify the roles / functions of brain
regions)

Cognitive Science Focus
- Comparisons with behavioral (e.g. priming experiments, eye-tracking,
self-paced reading) and elicited data (e.g. semantic feature norms)
- Biologically plausible connectionist approaches

Shared Data-Sets:
Submissions based on any data-sets or tasks are welcomed, and originality of
approach is encouraged. However, to assist researchers who are new to this
topic, we are providing the data used in Mitchell et al. (2008) and Murphy et
al. (2009), as well as a number of sample shared tasks. Submissions are welcome
that follow the tasks in whole or in part, or simply to use them as an
evaluation baseline for their own work. Performance will not be independently
validated by the organizers, and will only be one of the criteria used to select
among submissions.

The CMU fMRI data-set of 60 concrete concepts, in 12 categories, collected while
nine English speakers were presented with 60 line drawings of objects with text
labels and were instructed to think of the same properties of the stimulus
object consistently during each presentation. For each concept there are 6
instances of ~20k neural activity features (brain blood oxygenation levels):
http://www.cs.cmu.edu/%7Ekkchang/fMRI/data.html

The Trento EEG data-set for 60 concept concepts, in 2 categories (work tools and
land mammals), collected while seven Italian speakers were silently naming
photographic images that represent these concepts. For each concept there are 6
instances of ~15k neural activity features (spectral power in voltage signals):
http://clic.cimec.unitn.it/brian/compNeuroWSnaacl10/

Sample Shared Tasks:
As noted above, submissions on any task are welcomed, and these tasks are
primarily intended to provide a possible starting point for researchers who are
new to the topic.

Concept-pair neural discrimination task: For two concepts randomly left out of
training, teach a classifier to match recorded neural data to the correct
lexeme. This may be achieved by taking advantage of corpus-based models of word
meaning, as in published research, or otherwise. This task is based on the
evaluation method used with fMRI data in Mitchell et al. (2008), and replicated
with EEG data in Murphy et al. (2009).

Corpus semantic model evaluation task: Teach a classifier to predict the neural
activity observed for single concepts, based on each of several corpus semantic
models. The average similarity between observed activity and predicted activity
over all concepts can be taken as metric of corpus model fidelity.

Important Dates:
March 1, 2010: Deadline for submission of workshop papers
March 30, 2010: Notification of acceptance
April 12, 2010: Camera-ready papers due
June 5 or 6, 2010: Workshop date

Submissions:
Authors are invited to submit full papers on original, unpublished work in the
topic area of this workshop via the NAACL submission site:
https://www.softconf.com/naaclhlt2010/neuroling/

Submissions should be formatted using the NAACL 2010 stylefiles, with blind
review and not exceeding 8 pages plus an extra page for references. The
stylefiles are available at http://naaclhlt2010.isi.edu/authors.html. The PDF
files will be submitted electronically through the NAACL submission system, the
link will be available later. Each submission will be reviewed at least by two
members of the programme committee. Accepted papers will be published in the
workshop proceedings. Dual submissions to the main NAACL 2010 conference and
this workshop are allowed; if you submit to the main session, indicate this when
you submit to the workshop. If your paper is accepted for the main session, you
should withdraw your paper from the workshop upon notification by the main session.

Organisers:
Brian Murphy, brian.murphyunitn.it, Centre for Mind/Brain Studies,
University of Trento
Kai-min Kevin Chang, kaimin.changgmail.com, Language Technologies
Institute, Carnegie Mellon University
Anna Korhonen, alk23cam.ac.uk, Computer Laboratory, University of Cambridge

Program Committee:
- Afra Alishahi, Saarland University, Germany
- Afra Alishahi, Saarland University, Germany
- Ben Amsel, University of Toronto, Canada
- Stefano Anzellotti, Harvard University, USA
- Colin Bannard, University of Texas Austin, USA
- Marco Baroni, University of Trento, Italy
- Gemma Boleda, Universitat Politècnica de Catalunya, Spain
- Ina Bornkessel, Max Planck Leipzig, Germany
- Augusto Buchweitz, Carnegie Mellon University, USA
- George Cree, University of Toronto, Canada
- Barry Devereux, University of Cambridge, UK
- Katrin Erk, University of Texas Austin, USA
- Stefan Evert, Unversity of Osnabrück, Germany
- Adele Goldberg, Princeton University, USA
- Chu-Ren Huang, Hong Kong Polytechnic University, Hong Kong
- Aravind Joshi, University of Pennsylvania, USA
- Marcel Just, Carnegie Mellon University, USA
- Frank Keller, University of Edinburgh, UK
- Charles Kemp, Carnegie Mellon University, USA
- Mirella Lapata, University of Edinburgh, UK
- Chia-Ying Lee, Academia Sinica, Taiwan
- Roger Levy, University of California Sand Diego, USA
- Angelika Lingnau, University of Trento, Italy
- Brad Mahon, University of Rochester, USA
- Robert Mason, Carnegie Mellon University, USA
- Diana McCarthy, Lexical Computing Ltd, UK
- Ken McRae, University of Western Ontario, Canada
- Tom Mitchell, Carnegie Mellon University, USA
- Fermin Moscoso del Prado Martin, University of Provence, France
- Sebastian Padò, University of Stuttgart, Germany
- Francisco Periera, Princeton University, USA
- Massimo Poesio, University of Trento, Italy
- Thierry Poibeau, University of Paris 13, France
- Dean Pomerleau, Intel Labs Pittsburgh, USA
- Ari Rappoport, Hebrew University of Jerusalem, Israel
- Brian Roark, Oregeon Health & Science University, USA
- Kenji Sagae, University of Southern California, USA
- Hinrich Schütze, Stuttgart University, Germany
- Sabine Schulte im Walde, University of Stuttgart, Germany
- Svetlana Shinkareva, University of South Carolina, USA
- Nathaniel Smith, University of San Diego, USA
- Aline Villavicencio, Federal University of Rio Grande do Sul, Brazil
- David Vinson, University College London, UK
- Yang ChinLung, City University of Hong Kong, China
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