English(EN) Batched Speech Decisions Without Decoding: Single-Token Supervision Lets a Frozen LLM Hear Beyond the Transcript

DuplexJev系统使冻结的LLM能够超越文本记录进行聆听

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-02 00:00

研究人员推出了一种名为DuplexJev的新颖系统，旨在提高全双工语音代理的效率。与传统的缓慢解码不同，DuplexJev将自动语音识别（ASR）编码器的隐藏状态通过一个小型连接器输入到冻结的大型语言模型（LLM）中。这使得系统能够在大约0.1秒内对八个话语做出多个决策，速度远超以往的方法。该系统还展示了识别说话者情绪和性别的能力，准确率达到90%，并且已发布权重和训练流程。 AI

影响通过使冻结的LLM能够快速处理语音决策并理解非文本记录的线索，提高了语音代理的效率和能力。

排序理由该条目是一篇研究论文，详细介绍了一种用于语音代理的新系统，包括模型权重和训练方法。[lever_c_research降级：ic=1 ai=1.0]

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-10-02 00:00

无需解码的批量语音决策：单Token监督让冻结的LLM听懂超越文本的内容

Full-duplex voice agents make many small, closed decisions, which current systems answer by slow autoregressive decoding. We propose DuplexJev, which feeds ASR-encoder hidden states through a small connector into a frozen LLM and reads each question as a single-token distribution…

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无需解码的批量语音决策：单Token监督让冻结的LLM听懂超越文本的内容

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