mlsanityData to 14 Oct 2026

Seed LiveInterpret 2.0: End-to-end Simultaneous Speech-to-speech Translation with Your Voice

arXiv 2507.17527 ↗First posted 23 Jul 2025cs.CL cs.SD eess.AScited by 9

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Abstract (arXiv)

Simultaneous Interpretation (SI) represents one of the most daunting frontiers in the translation industry, with product-level automatic systems long plagued by intractable challenges: subpar transcription and translation quality, lack of real-time speech generation, multi-speaker confusion, and translated speech inflation, especially in long-form discourses. In this study, we introduce Seed-LiveInterpret 2.0, an end-to-end SI model that delivers high-fidelity, ultra-low-latency speech-to-speech generation with voice cloning capabilities. As a fully operational product-level solution, Seed-LiveInterpret 2.0 tackles these challenges head-on through our novel duplex speech-to-speech understanding-generating framework. Experimental results demonstrate that through large-scale pretraining and reinforcement learning, the model achieves a significantly better balance between translation accuracy and latency, validated by human interpreters to exceed 70% correctness in complex scenarios. Notably, Seed-LiveInterpret 2.0 outperforms commercial SI solutions by significant margins in translation quality, while slashing the average latency of cloned speech from nearly 10 seconds to a near-real-time 3 seconds, which is around a near 70% reduction that drastically enhances practical usability.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 43 of its 51 references that are in the map. First posted on arXiv 23 Jul 2025.

Builds on

43 of 51 references.

References · 43

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  12. 2024Seed-TTS: A Family of High-Quality Versatile Speech Generation Modelscited by 300
31 more
  1. 2024ReFT: Reasoning with Reinforced Fine-Tuningcited by 239
  2. 2024Tower: An Open Multilingual Large Language Model for Translation-Related Taskscited by 206
  3. 2023Seamless: Multilingual Expressive and Streaming Speech Translationcited by 192
  4. 2025Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learningcited by 161
  5. 2019Direct speech-to-speech translation with a sequence-to-sequence modelcited by 118
  6. 2019Monotonic Infinite Lookback Attention for Simultaneous Machine Translationcited by 104
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  9. 2024Multi-turn Reinforcement Learning from Preference Human Feedbackcited by 67
  10. 2024Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognitioncited by 63
  11. 2020Efficient Wait-k Models for Simultaneous Machine Translationcited by 61
  12. 2022Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translationcited by 57
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  22. 2024Speech Translation with Speech Foundation Models and Large Language Models: What is There and What is Missing?cited by 23
  23. 2024StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learningcited by 21
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  31. 2025CMU's IWSLT 2025 Simultaneous Speech Translation Systemcited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 8.

9 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025Cross-Lingual F5-TTS: Towards Language-Agnostic Voice Cloning and Speech Synthesis
  2. 2025SimulMEGA: MoE Routers are Advanced Policy Makers for Simultaneous Speech Translation
  3. 2026One Voice, Many Tongues: Cross-Lingual Voice Cloning for Scientific Speech
  4. 2022Sample, Translate, Recombine: Leveraging Audio Alignments for Data Augmentation in End-to-end Speech Translation
  5. 2025UniSS: Unified Expressive Speech-to-Speech Translation with Your Voice
  6. 2025Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters
  7. 2023Improving End-to-End Speech Translation by Imitation-Based Knowledge Distillation with Synthetic Transcripts
  8. 2026KIT's Submission to Cross-Lingual Voice Cloning in IWSLT 2026