Creation and Detection of German Voice Deepfakes
- Synthesizing voice with the help of machine learning techniques has made rapid progress over the last years. Given the current increase in using conferencing tools for online teaching, we question just how easy (i.e. needed data, hardware, skill set) it would be to create a convincing voice fake. We analyse how much training data a participant (e.g. a student) would actually need to fake anotherSynthesizing voice with the help of machine learning techniques has made rapid progress over the last years. Given the current increase in using conferencing tools for online teaching, we question just how easy (i.e. needed data, hardware, skill set) it would be to create a convincing voice fake. We analyse how much training data a participant (e.g. a student) would actually need to fake another participants voice (e.g. a professor). We provide an analysis of the existing state of the art in creating voice deep fakes and align the identified as well as our own optimization techniques in the context of two different voice data sets. A user study with more than 100 participants shows how difficult it is to identify real and fake voice (on avg. only 37% can recognize a professor’s fake voice). From a longer-term societal perspective such voice deep fakes may lead to a disbelief by default.…
Document Type: | Conference Proceeding |
---|---|
Conference Type: | Konferenzartikel |
Zitierlink: | https://opus.hs-offenburg.de/6685 | Bibliografische Angaben |
Title (English): | Creation and Detection of German Voice Deepfakes |
Conference: | FPS: International Symposium (14. : December 7-10, 2021 : Paris, France) |
Author: | Vanessa Barnekow, Dominik BinderStaff MemberGND, Niclas Kromrey, Pascal Munaretto, Andreas SchaadStaff MemberGND, Felix Schmieder |
Edition: | 1. |
Year of Publication: | 2022 |
Place of publication: | Cham |
Publisher: | Springer |
First Page: | 355 |
Last Page: | 364 |
Parent Title (English): | Foundations and Practice of Security |
Editor: | Esma Aïmeur, Maryline Laurent, Reda Yaich, Benoît Dupont, Joaquin Garcia-Alfaro |
Volume: | LNCS 13291 |
ISBN: | 978-3-031-08146-0 (Softcover) |
ISBN: | 978-3-031-08147-7 (eBook) |
ISSN: | 0302-9743 |
ISSN: | 1611-3349 (E-ISSN) |
DOI: | https://doi.org/10.1007/978-3-031-08147-7_24 |
Language: | English | Inhaltliche Informationen |
Institutes: | Fakultät Medien (M) (ab 22.04.2021) |
Institutes: | Bibliografie |
Tag: | Deepfake | Formale Angaben |
Relevance: | Konferenzbeitrag: h5-Index < 30 |
Open Access: | Closed |
Licence (German): | Urheberrechtlich geschützt |