AI 说话前先猜你要说什么，响应快 73%
现在的语音 AI 是「听一段、想一段、说一段」，你话还没说完它只能干等，所以每次对话都有半秒以上的停顿。这篇论文发现一个反直觉的事实：在 95.3% 的情况下，AI 就算没听到你下一句，也能猜对你要说什么——它干脆在空闲时先按「沉默」把回答草稿写好，等真音频来了再核对，错了就改。这套方法不用重新训练、不损失准确率，把响应延迟从秒级压到 74-241 毫秒，接近真人对话 200 毫秒的接话间隔。它不是你明天就能用上的功能，但这是语音助手从「一问一答」走向「边听边说」的关键一步。
📄 原文摘要(英文)
Chunk-interleaved full-duplex speech language models listen and speak in fixed time chunks, and each chunk must be processed before the next one arrives. Their workload is asymmetric across chunks: listen chunks leave compute idle while awaiting audio, and speak and tool-call chunks require serial generation, which delays responses and tool calls. Using the idle compute for the next chunk requires decoding it before its audio arrives, under an assumed input. Taking silence as the assumed input and comparing the output with the output under real audio on four models, we observe two properties. First, the next audio chunk does not change the output in 95.3% of chunks. Second, 88% of changes begin at the first output token. Building on these properties, we propose Speculative Listening, a training-free, lossless framework for input-time self-speculative decoding. During idle time, the model drafts the next chunk under silence and, for changes at the first token, a second branch from the runner-up first token. It keeps all drafts in a cross-chunk hypothesis pool and verifies them when the audio arrives. On our eight-task benchmark TickTock-Bench, Speculative Listening speeds up speak chunks by 2.6-2.8x and tool-call chunks by up to 23.4x. On average, it reduces the decoding delay before a response starts by 73%, to 74-241 ms, close to the 200 ms gap between human turns, and the maximum lag behind real time by 94.4%.