Final Call For Papers
(EMNLP/VLC-99) JOINT SIGDAT CONFERENCE ON
EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING AND
VERY LARGE CORPORA
This SIGDAT-sponsored joint conference will continue to provide a forum for new research in corpus-based and/or empirical methods in NLP. In addition to providing a general forum, the theme for this year is
"Corpus-based and/or Empirical Methods in NLP for Speech, MT, IR, and other Applied Systems"
A large number of systems in automatic speech recognition(ASR) and synthesis, machine translation(MT), information retrieval(IR), optical character recognition(OCR) and handwriting recognition have become commercially available in the last decade. Many of these systems use NLP technologies as an important component. Corpus-based and empirical methods in NLP have been a major trend in recent years. How useful are these techniques when applied to real systems, especially when compared to rule-based methods? Are there any new techniques to be developed in EMNLP and from VLC in order to improve the state-of-the-art of ASR, MT, IR, OCR, and other applied systems? Are there new ways to combine corpus-based and empirical methods with rule-based systems?
This two-day conference aims to bring together academic researchers and industrial practitioners to discuss the above issues, through technical paper sessions, invited talks, and panel discussions. The goal of the conference is to raise an awareness of what kind of new EMNLP techniques need to be developed in order to bring about the next breakthrough in speech recognition and synthesis, machine translation, information retrieval and other applied systems.
The conference solicits paper submissions in (and not limited to) the following areas:
1) Original work in one of the following technologies and its relevance
to speech, MT, or IR:
(a) word sense disambiguation
(b) word and term segmentation and extraction
(d) bilingual lexicon extraction
(e) POS tagging
(f) statistical parsing
(g) dialog models
(h) others (please specify)
2) Proposals of new EMNLP technologies for speech, MT, IR, OCR, or other applied systems (please specify).
3) Comparetive evaluation of the performance of EMNLP technologies in one of the areas in (1) and that of its rule-based or knowledge-based counterpart in a speech, MT, IR, OCR or other applied system.
Submissions should be limited to original, evaluated work. All papers should include background survey and/or reference to previous work. The authors should provide explicit explanation when there is no evaluation in their work. We encourage paper submissions related to the conference theme. In particular, we encourage the authors to include in their papers, proposals and discussions of the relevance of their work to the theme. However, there will be a special session in the conference to include corpus-based and/or empirical work in all areas of natural language processing.
Only hard-copy submissions will be accepted. Reviewing of papers will not be blind. The submission format and word limit are the same as those for ACL this year. We strongly recommend the use of ACL-standard LaTeX (plus bibstyle and trivial example) or Word style files for the preparation of submissions. Paper ID is not required. Please leave it blank. Six opies of full-length paper (not to exceed 3200 words exclusive of references) should be received at the following address before or on March 31, 1999.
EMNLP/VLC-99 Program Committee
c/o Pascale Fung
Department of Electrical and Electronic Engineering
University of Science and Tehnology (HKUST)
Clear Water Bay, Kowloon
Submission of full-length paper
April 30 Acceptance notice
May 20 Camera-ready paper due
June 21-22 Conference date
Jing-Shin Chang (Behavior Design Corp.)
Ken Church (AT&T Labs--Research)
Ido Dagan (Bar-Ilan University)
Marti Hearst (UC-Berkeley)
Huang, Changning (Tsinghua University)
Pierre Isabelle (Xerox Research Europe)
Lillian Lee (Cornell University)
David Lewis (AT&T Research)
Dan Melamed (West Group)
Mehryar Mohri (AT&T Labs--Research)
Masaaki Nagata (NTT)
Richard Sproat (AT&T Labs--Research)
Andreas Stolcke (SRI)
Ralph Weischedel (BBN)
Dekai Wu (Hong Kong University of Science & Technology)
David Yarowsky (Johns Hopkins University)