BeaverTalk: Oregon State University’s IWSLT 2025 Simultaneous Speech Translation System
Matthew Raffel, Victor Agostinelli, Lizhong Chen · 2025
This paper discusses the construction, finetuning, and deployment of BeaverTalk 1 , a cascaded system for speech-to-text translation as part of the IWSLT 2025 simultaneous translation task.The system architecture employs a VAD segmenter for breaking a speech stream into segments, Whisper Large V2 for automatic speech recognition (ASR), and Gemma 3 12B for simultaneous translation.Regarding the simultaneous translation LLM, it is fine-tuned via low-rank adaptors (LoRAs) for a conversational prompting strategy that leverages a single prior-sentence memory bank from the source language as context.The cascaded system participated in the English→German and English→Chinese language directions for both the low and high latency regimes.In particular, on the English→German task, the system achieves a BLEU of 24.64 and 27.83 at a StreamLAAL of 1837.86 and 3343.73,respectively.Then, on the English→Chinese task, the system achieves a BLEU of 34.07 and 37.23 at a StreamLAAL of 2216.99 and 3521.35,respectively.