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Call Deadline: 15-Oct-2012

Call Information:
First Call for Papers

Managing Noise in the Signal: Error Handling in Natural Language Processing

A special issue of the Traitement Automatique des Langue (TAL) journal

The language that real-world natural language processing systems have to
deal with bears little resemblance to the perfectly grammatical examples
often found in linguistics textbooks. Instead, it comes to us damaged in
various ways: authors introduce spelling and grammatical errors into the texts
they type, speakers produce incomplete or otherwise disfluent sentences,
OCR systems misrecognize the characters on the printed page, and speech
recognition systems produce inaccurate hypotheses as to what was actually

Noisy input is a fact of life: our systems ignore it at their peril. For some
applications, we require mechanisms which are robust to error; for example, a
spoken language dialog system may assign a low confidence to a
hypothesis, and as a consequence ask the user to repeat his/her utterance.
For other applications, we need to make use of error correction techniques,
so that, for example, an OCR system might use contextual post-processing
to validate the spellings of words.

This special issue aims to bring together work on error handling in natural
language processing from a range of different application areas. Many
subfields of NLP have a need to do something about noise in the signal, but
rarely do researchers from these diverse areas have an opportunity to
compare their methods and techniques. Our aim is to juxtapose work from
these different areas in order to encourage cross-fertilization of ideas.

We consider as in-scope for this special issue any papers which describe and
discuss techniques that are concerned with processing linguistic data which
are in some regard noisy. The most developed subfields here are spelling
correction and, to a lesser extent, grammar correction; neither of these are
completely solved problems, and as far as errors at the stylistic, semantic,
and discourse levels are concerned, automated textual error correction has
barely scratched the surface. Robust processing regimes, where the aim is to
extract something useful from a broken input, are also of interest, for both
speech and text input; and more broadly, repair and recovery techniques in
dialog systems are also of relevance.

We encourage submissions on any aspect of natural language processing
related to the handling of errors, including in particular:
* automatic spelling and grammar correction
* semantic and logical errors
* stylistic and discourse-level correction
* automatic correction of machine-produced texts (OCRs, speech transcripts,
* spelling correction in web search
* errors in controlled language input
* acquisition, annotation and analysis of errors in real texts
* errors in language learning
* handling performance errors
* building error corpora
* text normalization issues
* robust NLP techniques
* handling disfluent speech
* handling errors in speech recognition
* confidence measure estimation
* managing noise in training corpora
* error metrics
* error as signatures; watermarking with errors
* measuring the seriousness of errors

Guest Editors:
- Robert Dale (Macquarie University, Australia)
- Fran├žois Yvon (LIMSI/CNRS and Univ. Paris Sud, France)

Important Dates:
- Submission: 15/10/2012
- First notification to authors: 15/12/2012
- Revisions: 01/02/2013
- Final decisions: 15/04/2013
- Camera-ready: 15/06/2013
- Publication: Summer 2013

Practical Issues:
Refer to