English(EN) GIVE-KWS: Gated Injection of Visual Evidence for Noise-Robust Query-by-Example Keyword Spotting

新的 GIVE-KWS 系统使用视觉语音来提高噪声鲁棒的关键词识别

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 04:00

研究人员开发了 GIVE-KWS，一个利用视觉语音线索来提高噪声鲁棒性的关键词识别新系统。通过引入门控交叉注意力机制，GIVE-KWS 将查询音频与唇部运动相结合，展示了显著的性能提升。与基准系统相比，该系统在 -10 dB 信噪比下实现了 72.9% 的未见关键词错误率降低，突显了视觉表示中的音素信息对于有效噪声鲁棒性的重要性。 AI

影响增强了语音识别系统在嘈杂环境中的鲁棒性，可能改善真实世界应用中的用户体验。

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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Ming-Hsiang Hu, Kuan-Tang Huang, Hung-Shin Lee, Berlin Chen · 2026-10-07 04:00

GIVE-KWS: 用于噪声鲁棒性按示例查询关键词识别的门控视觉证据注入

arXiv:2610.07046v1 Announce Type: cross Abstract: Visual speech promises noise-robust keyword spotting, yet a visual stream is not necessarily used. On a tri-modal query-by-example keyword spotting (QbyE-KWS) benchmark, we find that a system with a task-trained visual encoder com…

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报道来源 [1]

GIVE-KWS: 用于噪声鲁棒性按示例查询关键词识别的门控视觉证据注入

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