[iva] [Call for Papers] ICASSP 2024 Workshop - Trustworthy Speech Processing

[Anil Ramakrishna]

Please circulate among your teams.

Inviting submissions for (hybrid) ICASSP 2024 Workshop on Trustworthy
Speech Processing (TSP)


Submission deadlines:

  January 20th, 2024, AoE (to be considered for archival on IEEE Xplore)

  February 20th, 2024 AoE (non-archival)

Author Notification: Two weeks after each deadline above

Workshop Date: TBD
Workshop Website: trustworthyspeechprocessing.github.io

Overview
Given the ubiquity of Machine Learning (ML) systems and their relevance in
daily lives, it is important to ensure private and safe handling of data
alongside equity in human experience. These considerations have gained
considerable interest in recent times under the realm of Trustworthy ML.
Speech processing in particular presents a unique set of challenges, given
the rich information carried in linguistic and paralinguistic content
including speaker trait, interaction and state characteristics including
health status. In this workshop on Trustworthy Speech Processing (TSP), we
aim to bring together new and experienced researchers working on
trustworthy ML and speech processing. We invite novel and relevant
submissions from both academic and industrial research groups showcasing
theoretical and empirical advancements in TSP.

Call for Papers
We invite novel and unpublished research publications (negative results are
welcome too) as well as position papers from any topic in Trustworthy
Speech Processing (including ones listed above). Submissions should follow
the official ICASSP template
<https://cmsworkshops.com/ICASSP2024/papers/paper_kit.php> and include a
maximum of 4 pages of technical content followed by references. However,
you are welcome to include supplementary material of any length after
references.

Topics of interest cover a variety of papers centered on speech processing,
including (but not limited to):

   1.

   Differential privacy
   2.

   Bias and Fairness
   3.

   Federated learning
   4.

   Ethics in speech processing
   5.

   Model interpretability
   6.

   Quantifying & mitigating bias in speech processing
   7.

   New datasets, frameworks and benchmarks for TSP
   8.

   Discovery and defense against emerging privacy attacks
   9.

   Trustworthy ML in applications of speech processing like ASR

Submissions are managed via OpenReview, please submit your papers here
<https://openreview.net/group?id=ICASSP/2024/Workshop/TSP>. Authors have an
option to publish their papers in IEEE Xplore (archival mode); if you wish
to do this, please submit before January 20th.


*We will also support remote presentations* in case you are unable to
travel in person.


Organizers
Anil Ramakrishna, Amazon Inc.; Shrikanth Narayanan, University of Southern
California; Rahul Gupta, Amazon Inc.; Isabel Trancoso, University of
Lisbon; Bhiksha Raj, Carnegie Mellon University; Theodora Chaspari, Texas
A&M University.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.uni-bielefeld.de/mailman2/unibi/public/iva-list/attachments/20231207/93f54ee5/attachment.html>