  This paper presents CrossVoice, a novel cascade-based Speech-to-Speech
Translation (S2ST) system employing advanced ASR, MT, and TTS technologies with
cross-lingual prosody preservation through transfer learning. We conducted
comprehensive experiments comparing CrossVoice with direct-S2ST systems,
showing improved BLEU scores on tasks such as Fisher Es-En, VoxPopuli Fr-En and
prosody preservation on benchmark datasets CVSS-T and IndicTTS. With an average
mean opinion score of 3.75 out of 4, speech synthesized by CrossVoice closely
rivals human speech on the benchmark, highlighting the efficacy of
cascade-based systems and transfer learning in multilingual S2ST with prosody
transfer.
