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SimulTron: On-Device Simultaneous Speech to Speech Translation

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arxiv 2406.02133 v1 pith:JTBOPVMY submitted 2024-06-04 eess.AS cs.CLcs.LGcs.SD

Alex Agranovich , Eliya Nachmani , Oleg Rybakov , Yifan Ding , Ye Jia , Nadav Bar , Heiga Zen , Michelle Tadmor Ramanovich This is my paper · ORCID
classification eess.AScs.CLcs.LGcs.SD
keywords simultrons2streal-timesimultaneoustranslationtranslatotronevaluationson-device
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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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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Spatial Speech Translation: Translating Across Space With Binaural Hearables

    cs.CL 2025-04 conditional novelty 6.0 of 10

    Spatial speech translation preserves speaker direction and voice characteristics in real-time binaural hearable translation, achieving ASR-BLEU up to 22.07 under interfering speakers.

  2. Direct Speech-to-Speech Neural Machine Translation: A Survey

    cs.CL 2024-11 conditional novelty 4.0 of 10

    A survey of direct speech-to-speech translation models, with a taxonomy of offline, simultaneous, and LLM-based systems and a small new benchmark comparison on CVSS-C.

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