研究人员推出SelectTSL，这是一种新颖的端到端架构，专为复杂声学环境中的提示引导式选择性声音定位而设计。该系统通过提取目标声音并保留空间信息以实现精确本地化，克服了现有方法的局限性。SelectTSL利用提示引导式选择性注意力模块生成受提示信息影响的嵌入，然后这些嵌入会精炼相位线索并估计到达方向和声源基数，从而有效地关注用户指定的空间线索并处理不同数量的目标声源。 AI
影响 引入了一种新的选择性声音定位方法，有望提高AI在嘈杂环境中聚焦特定音频源的能力。
排序理由 详细介绍新AI模型和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2607.02343v1 Announce Type: cross Abstract: Humans can selectively attend to a target sound and estimate its direction in complex scenarios, whereas such selective localization remains challenging for current deep learning-based systems. Sound source localization (SSL) has …
Humans can selectively attend to a target sound and estimate its direction in complex scenarios, whereas such selective localization remains challenging for current deep learning-based systems. Sound source localization (SSL) has achieved remarkable success with deep learning, ye…