“Big Data in Speech Computation”
Big Data is an emerging topic in a broad variety of research areas.
Especially deep learning methods gained huge successes in a broad area of
applications such as speech recognition, social signal analyses and natural
language processing. Big data furthermore allows to conduct predictive
analytics, user behaviour analytics to enhance the system knowledge on user
groups.
Along with the growing data and new methods also the problem of data
capturing, data storage and data analysis. Many of these issues demands a
manual annotation, which is not feasible in the case of big data. Thus,
methods to allow a proper (semi-)automatic annotation of big data are
needed.
On the other hand for emotional analyses and interaction analyses of speech
data the capturing of big data itself is challenging. Methods to generate
speech data from learned representations may help in this context.
In this special session we call for for research papers dealing and
discussing the above mentioned issues. The topics include (but are not limited
to):
deep learning,
transfer learning,
(semi-)automatic speech data analyses (for big data),
language modelling and big data
generative adversarial networks
Authors are asked to submit their papers using EasyChair submission system
https://easychair.org/conferences/?conf=specom2018
Accepted Special Session Papers will be published by within the Specom
Proceedings under Springer as a book in the Lecture Notes in Artificial
Intelligence (LNAI) series listed in all major citation databases such as
DBLP, SCOPUS, EI, INSPEC, COMPENDEX. SPECOM Proceedings are included in the
list of forthcoming proceedings for September 2018.
Organisers:
Anna Esposito (Università della Campnania “Luigi Vanvitelli”, Italy)
iiass.annaesp@tin.it
Friedhelm Schwenker (University Ulm, Germany)
friedhelm.schwenker@uni-ulm.de
Ingo Siegert (Otto von Guericke University Magdeburg, Germany)
ingo.siegert@ovgu.de