SLTC 2016 Program
16:30 – 16:45 Closing remarks
17:00 – 19:00 Welcome reception
Thursday, November 17
09:00 – 09:15 Opening
09:15 – 10:15 Keynote: Jill C. Burstein
Coee break
10:40 – 12.00 Session 1 Session 2
10:40 – 11.00 Sara Stymne. The Eect of Transla-
tionese on SMT Tuning
Per Fallgren, Jesper Segeblad and
Marco Kuhlmann. Towards a Standard
Dataset of Swedish Word Vectors
11:00 – 11.20 Simon Dobnik, Christine Howes and
John Kelleher. Towards a computational
model of frame of reference alignment
in Swedish dialogue
Lars Borin, Markus Forsberg, Mar-
tin Hammarstedt, Dan Rosén, Anne
Schumacher and Roland Schäfer.
Sparv: Språkbanken’s corpus annotation
pipeline infrastructure
11:20 – 11.40 Yuri Bizzoni and Simon Dobnik. Distri-
butional semantic models for detection
of textual entailment
Jenna Kanerva and Filip Ginter. An On-
line Tool for Discriminative Keyword Ex-
traction from Large Text Corpora
11:40 – 12.00 Niklas Zechner. A P reliminary Study on
Text-Based Music Generation
Karin Friberg Heppin and Dana Dan-
nélls. Guest s and hosts - Achieving clar-
ity in vagueness in Swedish FrameNet
Lunch
13:00 – 14:00 Keynote: Mehryar Mohri
14:00 – 15.20 Session 3, Chair: S. Stymne
14:00 – 14.20 Elena Volodina, Beata Megyesi, Mats Wirén, Lena Granstedt, Julia Prentice, Mon-
ica Reichenberg and Gunlög Sundberg. A Friend in Need? Research agenda for
electronic Second Language infrastructure
14:20 – 14.40 Fabienne Cap, Yvonne Adesam, Lars Ahrenberg, Lars Borin, Gerlof Bouma,
Markus Forsberg, Viggo Kann, Robert Östling, Aaron Smith, Mats Wirén and
Joakim Nivre. SWORD: Towards Cutting-Edge Swedish Word Processing
14:40 – 15.00 Robert Östling. Shallow Learning for sequence tagging
15:00 – 15.20 Viggo Kann. Blir studenternas språk sämre?
Coee break
15:40 – 17.00 Poster session
Dimitrios Kokkinakis, Kristina Lundholm Fors, Eva Björkner and Arto Nordlund.
Specifications and Methodology for Language-Related Data Acquisition and Analy-
sis in the Domain of Dementia Diagnostics
Marcus Klang and Pierre Nugues. Docforia: A Multilayer Document Model
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