# Simultaneous Translation with Offline Speech and LLM Models in CUNI Submission to IWSLT 2025

arXiv: https://arxiv.org/abs/2506.17077 · HTML: https://mlsanity.com/paper/2506.17077/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 16 references that are in the map.
- First posted on arXiv 20 Jun 2025.

## Builds on (most cited first, 9 of 9)

- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [Beyond English-Centric Multilingual Machine Translation](https://mlsanity.com/paper/2010.11125/) (2020)
- [EuroLLM: Multilingual Language Models for Europe](https://mlsanity.com/paper/2409.16235/) (2024)
- [AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation](https://mlsanity.com/paper/2305.11408/) (2023)
- [CUNI-KIT System for Simultaneous Speech Translation Task at IWSLT 2022](https://mlsanity.com/paper/2204.06028/) (2022)
- [Turning Whisper into Real-Time Transcription System](https://mlsanity.com/paper/2307.14743/) (2023)
- [StreamAtt: Direct Streaming Speech-to-Text Translation with Attention-based Audio History Selection](https://mlsanity.com/paper/2406.06097/) (2024)
- [How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation System?](https://mlsanity.com/paper/2412.18495/) (2024)
- [MT Metrics Correlate with Human Ratings of Simultaneous Speech Translation](https://mlsanity.com/paper/2211.08633/) (2022)

## Built on by (most cited first, 8 of 8)

- [Streaming Translation and Transcription Through Speech-to-Text Causal Alignment](https://mlsanity.com/paper/2603.11578/) (2026)
- [SimulU: Training-free Policy for Long-form Simultaneous Speech-to-Speech Translation](https://mlsanity.com/paper/2603.16924/) (2026)
- [A Pocket Offline Model for Simultaneous Speech Translation as CUNI Submission to IWSLT 2026](https://mlsanity.com/paper/2606.03948/) (2026)
- [AlignAtt4LLM: Fast AlignAtt for Decoder-Only LLMs at IWSLT 2026 Simultaneous Speech Translation Task](https://mlsanity.com/paper/2606.03967/) (2026)
- [Automatic Labelling of Speech Translation Errors](https://mlsanity.com/paper/2606.06047/) (2026)
- [MLLP-VRAIN UPV system for the IWSLT 2026 Simultaneous Speech Translation task](https://mlsanity.com/paper/2606.17255/) (2026)
- [Decoupling Turn-Taking from Semantics: A Decoupled Data Approach for Finite-State-Machine-Based Full-Duplex Dialogue](https://mlsanity.com/paper/2609.03321/) (2026)
- [Estimating Surprisal from the Speech Signal](https://mlsanity.com/paper/2610.18439/) (2026)

## Abstract (arXiv)

This paper describes Charles University submission to the Simultaneous Speech Translation Task of the IWSLT 2025. We cover all four language pairs with a direct or cascade approach. The backbone of our systems is the offline Whisper speech model, which we use for both translation and transcription in simultaneous mode with the state-of-the-art simultaneous policy AlignAtt. We further improve the performance by prompting to inject in-domain terminology, and we accommodate context. Our cascaded systems further use EuroLLM for unbounded simultaneous translation. Compared to the Organizers' baseline, our systems improve by 2 BLEU points on Czech to English and 13-22 BLEU points on English to German, Chinese and Japanese on the development sets. Additionally, we also propose a new enhanced measure of speech recognition latency.