Project description
Privacy-preserving smart speech technologies
The rise of smart speech technology has revolutionised consumer access to information and applications. However, privacy risks, including potential breaches by service operators and hackers accessing spoken words and sensitive non-lexical information, are a concern. Privacy-preserving smart speech technologies could help mitigate these risks. With the support of the Marie Skłodowska-Curie Actions programme, the PSST project aims to develop urgently needed technologies using deep learning. The project will focus on suppressing speaker traits in speech signals, enhancing usability between smart devices and cloud services, and creating novel evaluation schemes for relevant threats. It will establish a high-impact training programme to build expertise in speech processing, machine learning, and privacy-enhancing technologies.
Objective
The unabated rise of smart speech technology, much of which is operated by entities outside of the European Union, has revolutionised consumer access to information and applications using the most convenient interface of all - the human voice. Recently, however, we have come to understand that smart speakers, smartwatches and other voice-operated devices may expose their users to privacy risks. Service operators and hackers alike can access not only spoken words but may also exploit sensitive non-lexical information contained within speech signals (such as health status) for nefarious purposes without the users’ knowledge or consent.
However, innovative privacy-preserving smart speech technologies may mitigate these risks and help to create sustainable business models that are well aligned with EU regulations such as the GDPR and the forthcoming EU Artificial Intelligence (AI) Act. Therefore, the PSST joint doctoral training network will train a new cohort of researchers to develop these urgently-needed technologies using cutting-edge deep learning methods. PSST will focus on the suppression of speaker traits in speech signals, on enhancing usability in interactions between smart devices and cloud services, and on novel evaluation schemes that consider the most relevant threats. The PSST consortium is composed of world-leading research labs in speech processing, privacy and usability, and a larger number of innovative industrial partners. The joint academic-industrial partnership will establish a high-impact training programme that provides doctoral researchers with expertise in speech processing, machine learning and comprehensive knowledge of privacy threats and privacy-enhancing technologies.
PSST partners and researchers will jointly create not only a unique, user-centred view of smart speech technologies but will also promote innovative business models for responsible and sustainable privacy-aware technologies in the EU.
Fields of science
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Coordinator
02150 Espoo
Finland
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Participants (6)
06410 Biot
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1000 029 Lisboa
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78153 Le Chesnay Cedex
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44801 Bochum
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6525 XZ Nijmegen
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10623 Berlin
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Partners (14)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
75334 Paris
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
75013 Paris
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
66111 SAARBRUCKEN
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
02600 Espoo
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
75002 Paris
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
151 26 MAROUSI
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
92130 Issy Les Moulineaux
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91400 Orsay
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
1000-029 Lisboa
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
01067 Dresden
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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46003 Valencia
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1049 001 Lisboa
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
54052 Nancy Cedex
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
75006 Paris
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