arXiv:2606.03967cs.CLcs.AI2026-06中稿 · IWSLT 2026

首次将AlignAtt用于纯解码器大模型,实现低延迟同步翻译

AlignAtt4LLM: Fast AlignAtt for Decoder-Only LLMs at IWSLT 2026 Simultaneous Speech Translation Task

论文配图:AlignAtt4LLM: Fast AlignAtt for Decoder-Only LLMs at IWSLT 2026 Simultaneous Speech Translation Task
图 1 · 摘自论文原文
  • 在无编码器的解码器模型上重构对齐策略,通过提示词显式指定源端片段
  • 在英德、英意任务中,2秒低延迟下优于基线,4秒内延迟表现更优
  • 方法可复用于其他解码器模型,适合非欧洲语言的高速翻译场景

我们介绍AlignAtt4LLM,一种面向英语到德语、意大利语和中文的IWSLT 2026同步语音翻译系统。该系统为同步级联结构:Qwen3-ASR结合强制对齐生成增量更新的源端转写,Gemma-4 E4B-it在MT侧采用AlignAtt策略进行前缀翻译。据我们所知,这是首个将AlignAtt应用于纯解码器大模型的工作,此前系统依赖编码器-解码器交叉注意力,而本方法通过(1)显式在提示中加入源端片段,(2)离线选择翻译特定对齐头,(3)选择性qk-fast重放草稿-源注意力层,以及(4)运行时捕获查询/键以保持输出比特一致,成功恢复可用策略。在IWSLT 2026开发集上,该系统在英德、英意任务中均优于基线,尤其在约2秒低延迟及低于4秒的CU-LongYAAL高延迟条件下表现优异。中文任务结果较混杂,但方法不依赖Gemma-4:因AlignAtt4LLM仅需确定性提示布局、校准注意力头与查询/键捕获,同一策略可复用于更强的翻译专用解码器模型,适用于非欧洲语言。

原文摘要 · Abstract (English)

We describe AlignAtt4LLM, an IWSLT 2026 simultaneous speech translation system for English to German, Italian, and Chinese. The system is a synchronous cascade: Qwen3-ASR with forced alignment produces an incrementally updated source transcript, and Gemma-4 E4B-it translates that prefix under an MT-side AlignAtt policy. To our knowledge, this is the first application of AlignAtt to a decoder-only LLM, where the encoder-decoder cross-attention used by earlier AlignAtt systems is absent. We recover a usable policy by proposing (1) an explicit source span in the prompt, (2) offline selection of translation-specific alignment heads, (3) selective qk-fast replay of the draft-to-source attention block, and (4) runtime query/key capture that preserves model outputs bit-identically. On the IWSLT 2026 development set, AlignAtt4LLM outperforms the supplied baselines for the European target languages, English to German and English to Italian, in both the low-latency regime around 2 seconds and the high-latency regime below 4 seconds CU-LongYAAL. Results for English to Chinese are more mixed, but the method is not tied to Gemma-4: because AlignAtt4LLM only requires a deterministic prompt layout, calibrated attention heads, and query/key capture, the same policy can be reapplied to stronger translation-focused decoder-only MT backbones for non-European target languages.

同步翻译解码器模型对齐策略低延迟

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