MLLP-VRAIN UPV system for the IWSLT 2026 Simultaneous Speech Translation task
Quick Answer
This paper shows that The MLLP-VRAIN group employs Parakeet and Qwen 3.5 models for IWSLT 2026 Simultaneous Speech Translation, achieving a +5.82 improvement on the MCIF En→De test set.
Quick Take
Their new context track further enhances performance by +1.03 through ASR word-boosting and mechanisms.
Key Points
- Utilized Parakeet and Qwen 3.5 models for robust SimulST solutions.
- Participated in all language directions, including new context track.
- Achieved +5.82 improvement on MCIF En→De test set.
- Context track processing improved performance by +1.03.
- Implemented adaptive 'black-box' policies for better quality-latency trade-offs.
Paper Resources
Source Excerpt
arXiv:2606. 17255v1 Announce Type: new Abstract: This work describes the participation of the MLLP-VRAIN research group in the shared task of the IWSLT 2026 Simultaneous Speech Translation track. Our submission utilizes the recently released Parakeet and Qwen 3. 5 models to create a robust, cascaded solution for long-form SimulST through the use of adaptive "black-box" policies. We explore relaxations of these policies to achieve better quality-latency trade-offs.
Compared to last year, we participate on all language directions. …
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