Anonymizing Speaker Voices: Easy to Imitate, Difficult to Recognize?
Author:
Affiliation:
1. University of Southampton,UK
2. Fraunhofer AISEC
3. University of Avignon,France
4. Technical University Denmark,Denmark
Funder
Ministry of Economic Affairs
Nature
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10445798/10445803/10445935.pdf?arnumber=10445935
Reference33 articles.
1. An Unsupervised Method to Select a Speaker Subset from Large Multi-Speaker Speech Synthesis Datasets
2. An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning
3. How do Voices from Past Speech Synthesis Challenges Compare Today?
4. SHEEP, GOATS, LAMBS and WOLVES: a statistical analysis of speaker performance in the NIST 1998 speaker recognition evaluation
5. On speaker-independent, speaker-dependent, and speaker-adaptive speech recognition
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