SimulTron: On-Device Simultaneous Speech to Speech Translation

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.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10889296
Citations
2
Primary Topic
Speech Recognition and Synthesis
Type
article
Field-Weighted Citation Impact
4.96
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article

SimulTron: On-Device Simultaneous Speech to Speech Translation

Heiga Zen, Nadav Bar, Michelle Tadmor Ramanovich, Oleg Rybakov‎ et al.
2 citations
Speech Recognition and Synthesis
4.96
article

SimulTron: On-Device Simultaneous Speech to Speech Translation

Heiga Zen, Nadav Bar, Michelle Tadmor Ramanovich, Oleg Rybakov‎, Eliya Nachmani, Alex Agranovich, Jia Ye, Yifan Ding
article en
2 citations

Abstract

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.

Google (United States) (US), Google DeepMind (United Kingdom) (GB)
Openalex Percentile: Top 6%
Speech Recognition and Synthesis
4.96
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SimulTron: On-Device Simultaneous Speech to Speech Translation — Heiga Zen, Nadav Bar, et al. · (2025) | TGRS Research Map | TGRS