[iva] SLSP 2020: call for posters

IRDTA irdta at irdta.eu
Tue Sep 1 09:33:37 CEST 2020


SLSP 2020: call for posters*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*


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The 8th International Conference on Statistical Language and Speech Processing (SLSP 2020) invites researchers to submit poster presentations. SLSP 2020 will be held in Cardiff on October 14-16, 2020. See 


https://irdta.eu/slsp2020/


Poster presentations are intended to enhance informal interactions with conference participants, at the same time allowing for in-depth discussion.


TOPICS


Presentations displaying novel work in progress on statistical models (including machine learning) for language and speech processing are encouraged. Posters do not need to show final research results. Work that might lead to new interesting developments is welcome.


KEY DATES


Poster submission deadline: September 7, 2020


Notification of poster acceptance or rejection: September 14, 2020


SUBMISSION


Please upload a .pdf submission to:


https://easychair.org/conferences/?conf=slsp2020


It should contain the title, author(s) and affiliation, and should not exceed 500 words.


PRESENTATION


Posters will be allocated 10 minutes each in the programme for oral presentation. Moreover, they will remain hanging out during the whole conference for discussion.


PUBLICATION


Posters will not appear in the LNCS/LNAI proceedings volume of SLSP 2020. However, they will be eligible for submission to the post-conference journal special issue in Language Resources and Evaluation (Springer, JCR 2018 impact factor: 1.029).


REGISTRATION


At least one author of each accepted poster must register to the conference by September 21, 2020. The registration fare is reduced: 285 Euros. It gives the same rights all other conference participants will have (attendance, copy of the proceedings volume, coffee breaks, lunches). Contributors of regular papers who in addition get a poster accepted must register for the latter independently.

 
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