[iva] CfP: Security & Privacy in Speech Communication in EURASIP Journal on Audio, Speech, and Music Processing

[Ingo Siegert]

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*About*

In human communication, speech is a medium to impart and exchange 
information. Speech encodes a wealth of information on, e.g.: 
socio-economic background; racial, ethnic, and geographical origin; 
religious, political, and philosophical beliefs, health and emotion 
condition; identity; gender, and age. All of which is recognisable by 
humans. With speech technology evolving, machines are increasingly able 
to perceive and process this information. In certain usage scenarios, 
this specific information is needed to guarantee functionality and a 
proper service. But in many usage scenarios, this information is not 
needed and should be neglected.

For instance, detecting early signs of Parkinson’s disease, 
depression/suicide risk, and dementia help physicians sustain the health 
of a person by comprehensive medical profiling. In other circumstances, 
such profiling, while possible, is regarded as morally wrong indicating 
the importance of privacy in the context of speech analysis. Therefore, 
the terms Personally Identifiable Information (PII) and  Public Sector 
Information (PSI) are used. [Through PII as information representation, 
the identity of an individual can be reasonably inferred directly or 
indirectly. Information produced by public entities is PSI.] Regarding 
privacy in speech communication, we need not only to arrive at a better 
understanding of when speech data is seen as PII or PSI but also to 
which extent PII is needed for an application - and when we want to 
refrain from it.

We, furthermore, need to secure epistemic value across disciplines to 
arrive at a mannerism that is credible and adequate when designing 
speech & language technology (SLT) that respects fundamental human 
rights throughout product and service development, implementation, and 
integration. Moreover, the interoperability of privacy and security 
needs to be better understood. Security is used to countermeasure 
subversive users, such as detecting fake audio data in online banking 
using voice biometrics and call-center fraud prevention. Privacy is used 
to protect individuals from harm, e.g., through unbeknownst linkage of 
their (speech) data resulting in subsequent harm when harvested by 
adversaries. In the age of virtual voice assistants, speech 
communication is intimately related to daily life in digital societies, 
and so are security and privacy matters as well. Consequently, we need 
to also elaborate on how to involve the users and their perspectives on 
questions of privacy and security.

This special issue seeks to provide a venue for ongoing research in the 
recently formed research community on Security & Privacy in Speech 
Communication (SPSC), where views of technological and humanities 
communities nurture one another to develop multidisciplinary and 
interdisciplinary skills.

Technology and research need to aid individuals and society for which 
scientific inquiry needs to channel durable solutions. Currently, 
academic disciplines exist in silos; fields need to be bridged, and 
real-world problems to be solved. Ways to achieve this can be many in 
the anticipation of currently lacking multidisciplinary and 
interdisciplinary skill sets, e.g.: concise summaries of developments 
within a field for their relation to SLTs (hypothetical or existing); 
portrayals of community-driven efforts fostering security and/or privacy 
in SLTs; insights into the users’ ideas of the concepts and its effects 
on their usage; syntheses and analyses of SLT systems and continuous 
holistic improvement of their design, and security & privacy solutions 
for SLT applications including user experience(s).

The topics of interest for the special issue include, but are not 
limited to:

  * Sustainability and Economics
  * Secure/Private Speech Communication
  * Secure Computation and Cryptography
  * Psychology, e.g. media psychology and social psychology
  * Privacy-preserving Human-Computer Interfaces
  * Policy and Governance, Law, and Ethics
  * Natural Language Processing
  * Machine Learning for secure and private speech processing
  * Law Enforcement and Forensics
  * Information and Communication Technology for secure and private
    speech processing
  * Human-Computer Interaction Perspective on Security and Privacy
  * Digital Humanities and Anthropology regarding privacy and security needs

*Important Dates*
Submission deadline: 27 May 2022

*Lead Guest Editor*
Andreas Nautsch, /ISCA SIG SPSC, Germany/ and Rodrigo Capobianco Guido, 
/São Paulo State University, Brazil,/
Emails: guido at ieee.org

*Guest Editors*
Astrid Carolus, Julius-Maximilians University Würzburg, Germany
Hemant A. Patil, DA-IICT, India
Ingo Siegert, Otto-von-Guericke Universität Magdeburg, Germany

*Important*: Authors should select "/Security & Privacy in Speech 
Communication/" when they reach the “Article Type” step in the 
submission system.

*Submission instruction*: The submission system will open in early 
January 2022. Submissions deemed suitable will be reviewed by experts in 
different disciplines. Published articles will appear in different 
regular issues of the journal (clearly marked and branded as Special 
Issue articles. Please use IEEE style for citations; footnotes are neat 
for brief clarifications, and the layout should support reading (double 
column is a suggestion only). Write what prevails, make it digestible, 
and palate it to your audience of inquiry (impart knowledge, empower 
understanding, and take care of the willing reader to mature).

*Submisison guidelines*: 
https://asmp-eurasipjournals.springeropen.com/submission-guidelines

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