Tom Labiausse's research focuses on real-time speech translation and speech-to-speech translation models. His work aims to enable people speaking different languages to communicate naturally in real time through low-latency, expressive speech translation systems that preserve the speaker's characteristics.
After completing a double Master's degree in Computer Science and Machine Learning at CentraleSupélec and ENS Paris-Saclay (MVA), Tom joined Kyutai, where he contributed to the development of Hibiki, the first open-source simultaneous speech translation system to combine low latency with high-fidelity speech synthesis. The work was presented at ICML 2025.
Since 2025, he has been pursuing a PhD at Kyutai in partnership with the University of Avignon (LIA), where he continues to advance real-time speech translation. His recent work introduced Hibiki-Zero, an open-source multilingual speech-to-speech translation model that learns translation timing directly from sentence-level supervision and reinforcement learning instead of relying on interpretation-style training data, making simultaneous speech translation more scalable across languages. The work was presented at ICML 2026.