Simultaneous Translation with Offline Speech and LLM Models in CUNI Submission to IWSLT 2025
Year: 2025
Type: conference-paper
Abstract: 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.
Authors: Dominik Macháček, Peter Polák
Institution: Charles University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4412944354