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<font face="Arial">CALL FOR PAPERS<br>
<br>
Advances in Human-Computer Interaction<br>
Special Issue on Advancing Big Data in Speech Computation<br>
<br>
Hindawi <br>
</font><br>
<font face="Arial"><font face="Arial">Submission Deadline: Friday,
31 May 2019<br>
Publication Date: October 2019<br>
<br>
<br>
</font>Big Data is an emerging topic in a broad variety of
research areas, with the promise to allow predictive user behavior
analytics <br>
for a wide variety of speech patterns like emotions, sentiment,
personality, and pathology. With the emerging voice assistants, <br>
such as Amazon Alexa or Google Assistant, speech interaction has
attracted increasing attention. In addition, further speech-based
<br>
HCI-systems could benefit from big data computation, such as
Speech-to-Speech translation systems, conversational agents, <br>
and educational systems. Unfortunately, when dealing with speech
computation tasks, oen only comparably small amounts of <br>
data are available, or the collection is cumbersome.Thus, advanced
methods such as transfer learning, active learning, data <br>
synthesis, and (semi-)automatic annotation methods or
domain-/topic-adaptation are needed.<br>
<br>
This special issue welcomes original research papers concerned
with the big data exploitation of speech data, particularly in <br>
HCI-related contexts. We encourage researchers to submit review
articles describing the current state of the art in speech-based <br>
big-data analyses. Submissions dealing with data synthesis or
recordings and automatic annotation of large sets of speech <br>
data are highly encouraged.<br>
<br>
Potential topics include but are not limited to the following:<br>
* Speech data transfer learning and active learning for HCI
systems<br>
* (Semi-) Automatic speech data analyses for HCI systems<br>
* Big data language modeling for HCI systems<br>
* Generative adversarial networks for speech-based HCI behavior
analytics<br>
* Methods review for big data in advancing speech-based HCI<br>
* Comparison of big data and small data approaches for
speech-based HCI<br>
* Application of Big data methods for speech based HCI-systems<br>
<br>
Authors can submit their manuscripts through the Manuscript
Tracking System at
<a class="moz-txt-link-freetext" href="https://mts.hindawi.com/submit/journals/ahci/abd/">https://mts.hindawi.com/submit/journals/ahci/abd/</a>.<br>
<br>
Papers are published upon acceptance, regardless of the Special
Issue publication date.<br>
<br>
Lead Guest Editor<br>
Ingo Siegert, Otto von Guericke University, Magdeburg, Germany<br>
<a class="moz-txt-link-abbreviated" href="mailto:ingo.siegert@ovgu.de">ingo.siegert@ovgu.de</a><br>
<br>
Guest Editors<br>
Anna Esposito, Università della Campania "Luigi Vanvitelli",
Napoli, Italy<br>
<a class="moz-txt-link-abbreviated" href="mailto:anna.esposito@unicampania.it">anna.esposito@unicampania.it</a><br>
<br>
Friedhelm Schwenker, University of Ulm, Ulm, Germany<br>
<a class="moz-txt-link-abbreviated" href="mailto:friedhelm.schwenker@uni-ulm.de">friedhelm.schwenker@uni-ulm.de</a><br>
<br>
Gennaro Cordasco, Anna Esposito, Università della Campania "Luigi
Vanvitelli", Napoli, Italy<br>
<a class="moz-txt-link-abbreviated" href="mailto:gennaro.cordasco@unicampania.it">gennaro.cordasco@unicampania.it</a><br>
<br>
</font><br>
<pre class="moz-signature" cols="72">--
PD Dr. Friedhelm Schwenker
University of Ulm
Institute of Neural Information Processing
D-89069 Ulm, Germany
phone: +49-731-50-24159
fax: +49-731-50-24156
email: <a class="moz-txt-link-abbreviated" href="mailto:friedhelm.schwenker@uni-ulm.de">friedhelm.schwenker@uni-ulm.de</a>
www: <a class="moz-txt-link-freetext" href="http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/f-schwenker.html">http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/f-schwenker.html</a></pre>
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