  In recent years, there has been increased demand for speech-to-speech
translation (S2ST) systems in industry settings. Although successfully
commercialized, cloning-based S2ST systems expose their distributors to
liabilities when misused by individuals and can infringe on personality rights
when exploited by media organizations. This work proposes a regulated S2ST
framework called Preset-Voice Matching (PVM). PVM removes cross-lingual voice
cloning in S2ST by first matching the input voice to a similar prior consenting
speaker voice in the target-language. With this separation, PVM avoids cloning
the input speaker, ensuring PVM systems comply with regulations and reduce risk
of misuse. Our results demonstrate PVM can significantly improve S2ST system
run-time in multi-speaker settings and the naturalness of S2ST synthesized
speech. To our knowledge, PVM is the first explicitly regulated S2ST framework
leveraging similarly-matched preset-voices for dynamic S2ST tasks.
