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The GDPR & Speech Data: Reflections of Legal and Technology Communities, First Steps towards a Common Understanding

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arxiv 1907.03458 v1 pith:ODJQP65H submitted 2019-07-08 eess.AS cs.CY

classification eess.AScs.CY
keywords dataspeechgdprtechnologycommunitieslegalprivacyapplies
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Privacy preservation and the protection of speech data is in high demand, not least as a result of recent regulation, e.g. the General Data Protection Regulation (GDPR) in the EU. While there has been a period with which to prepare for its implementation, its implications for speech data is poorly understood. This assertion applies to both the legal and technology communities, and is hardly surprising since there is no universal definition of 'privacy', let alone a clear understanding of when or how the GDPR applies to the capture, storage and processing of speech data. In aiming to initiate the discussion that is needed to establish a level of harmonisation that is thus far lacking, this contribution presents some reflections of both legal and technology communities on the implications of the GDPR as regards speech data. The article outlines the need for taxonomies at the intersection of speech technology and data privacy - a discussion that is still very much in its infancy - and describes the ways to safeguards and priorities for future research. In being agnostic to any specific application, the treatment should be of interest to the speech communication community at large.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Do Not Mimic My Voice: Speaker Identity Unlearning for Zero-Shot Text-to-Speech

    cs.SD 2025-07 reject novelty 7.0 of 10

    Teacher-Guided Unlearning makes a zero-shot text-to-speech model ignore the audio prompt of designated speakers, generating a randomized voice instead, while keeping speech quality for other speakers.

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