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Workshop on Computational Neurolinguistics, NAACL HLT 2010, 5-6 Jun , 2010, Los Angeles, CA, USA

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
o Word-level analyses (e.g. corpus semantic models, lexica,
lexical relations and ontologies, parts-of-speech, word senses, morphology)
o Phrase-level analyses (e.g. word compounds, meaning
composition in multi-word expressions)
* Machine Learning Focus
o Decoding of cognitive states from neural activity
o Feature selection and data mining techniques for decoding
linguistic information
* Neural Science Focus
o Brain imaging techniques: fMRI, EEG, MEG, NIRS, including
cross-modality analysis (e.g. combining fMRI and EEG)
o Localizing Regions of Interest (e.g. identify the roles /
functions of brain regions)
* Cognitive Science Focus
o Comparisons with behavioral (e.g. priming experiments,
eye-tracking, self-paced reading) and elicited data (e.g. semantic
feature norms)
o 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/

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/