Simultaneous speech-to-speech translation (S2ST) holds the promise of
breaking down communication barriers and enabling fluid conversations across
languages. However, achieving accurate, real-time translation through mobile
devices remains a major challenge. We introduce SimulTron, a novel S2ST
architecture designed to tackle this task. SimulTron is a lightweight direct
S2ST model that uses the strengths of the Translatotron framework while
incorporating key modifications for streaming operation, and an adjustable
fixed delay. Our experiments show that SimulTron surpasses Translatotron 2 in
offline evaluations. Furthermore, real-time evaluations reveal that SimulTron
improves upon the performance achieved by Translatotron 1. Additionally,
SimulTron achieves superior BLEU scores and latency compared to previous
real-time S2ST method on the MuST-C dataset. Significantly, we have
successfully deployed SimulTron on a Pixel 7 Pro device, show its potential for
simultaneous S2ST on-device.

SimulTron 是一种轻量级的直接 S2ST 模型，通过在移动设备上进行实时评估，优于 Translatotron 1 的性能，并在 MuST-C 数据集上实现了优越的 BLEU 得分和延迟，展示了在 Pixel 7 Pro 设备上同时进行 S2ST 的潜力。