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Improving Voice Conversion for Dissimilar Speakers Using Perceptual Losses

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arxiv 2309.08263 v2 pith:EWAW2J4S submitted 2023-09-15 eess.AS cs.SD

classification eess.AScs.SD
keywords dataspeakerspeechvoiceconversiondevicesprotectionsecurity
verification ladder T0 review T1 audit T2 compute T3 formal

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The rising trend of using voice as a means of interacting with smart devices has sparked worries over the protection of users' privacy and data security. These concerns have become more pressing, especially after the European Union's adoption of the General Data Protection Regulation (GDPR). The information contained in an utterance encompasses critical personal details about the speaker, such as their age, gender, socio-cultural origins and more. If there is a security breach and the data is compromised, attackers may utilise the speech data to circumvent the speaker verification systems or imitate authorised users. Therefore, it is pertinent to anonymise the speech data before being shared across devices, such that the source speaker of the utterance cannot be traced. Voice conversion (VC) can be used to achieve speech anonymisation, which involves altering the speaker's characteristics while preserving the linguistic content.

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