CMU's IWSLT 2025 Simultaneous Speech Translation System

• URL: http://arxiv.org/abs/2506.13143v1
• Date: Mon, 16 Jun 2025 06:56:21 GMT
• Title: CMU's IWSLT 2025 Simultaneous Speech Translation System
• Authors: Siqi Ouyang, Xi Xu, Lei Li,
• Abstract summary: This paper presents CMU's submission to the IWSLT 2025 Simultaneous Speech Translation task.<n>Our end-to-end speech-to-text system integrates a chunkwise causal Wav2Vec 2.0 speech encoder, an adapter, and the Qwen2.5-7B-Instruct as the decoder.<n> Experimental results demonstrate that our system achieves 44.3 BLEU for English-to-Chinese and 25.1 BLEU for English-to-German.
• Score: 10.40867923457809
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents CMU's submission to the IWSLT 2025 Simultaneous Speech Translation (SST) task for translating unsegmented English speech into Chinese and German text in a streaming manner. Our end-to-end speech-to-text system integrates a chunkwise causal Wav2Vec 2.0 speech encoder, an adapter, and the Qwen2.5-7B-Instruct as the decoder. We use a two-stage simultaneous training procedure on robust speech segments curated from LibriSpeech, CommonVoice, and VoxPopuli datasets, utilizing standard cross-entropy loss. Our model supports adjustable latency through a configurable latency multiplier. Experimental results demonstrate that our system achieves 44.3 BLEU for English-to-Chinese and 25.1 BLEU for English-to-German translations on the ACL60/60 development set, with computation-aware latencies of 2.7 seconds and 2.3 seconds, and theoretical latencies of 2.2 and 1.7 seconds, respectively.

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