引导式测验 · 中等 等级

声音事件检测测验

研究声音类别和时间边界，包括复调、弱标签、DCASE 基线、起始容差和缺失类别注释。

相关引导路径声音事件检测
问题 1 的 8

时间声音事件检测除了片段级标签之外还估计哪些额外输出？

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  1. 时间声音事件检测除了片段级标签之外还估计哪些额外输出？
    • Only the audio file’s compression ratio
    • Only its filename’s alphabetical order
    • Event onset and offset boundaries within the clip
    • Only the display color of a waveform
  2. 为什么声音事件检测经常被描述为复调问题？
    • 因为它只处理音符
    • 因为多个声音可以重叠并同时出现
    • 因为它需要多个麦克风
    • 因为音频始终是立体声
  3. SED 训练数据中的“弱标签”是什么意思？
    • 标签已加密
    • 音频质量很差
    • 仅标记安静的声音
    • 剪辑被标记为事件发生，但不准确是在何时发生
  4. 在引用的 DCASE 2024 基线中识别了哪种分类器结构？
    • A convolutional recurrent neural network with added pretrained frame features
    • Only a static spreadsheet sort
    • Only an unchanged relational database table
    • Only a mandatory image-file compressor
  5. 在此描述的文档化声音检测基线上下文中使用了哪种时频表示？
    • Only a speech transcript
    • A log-mel representation
    • Only a JPEG photograph
    • Only an unchanged output filename
  6. Which cited research challenge supplies the 2018 and 2024 sound-event task settings discussed here?
    • 奥运会
    • A retail shopping holiday
    • A mandatory social-network ranking
    • DCASE
  7. Considering only the DCASE 2018 onset collar of 200 ms, does a 1.15 s prediction satisfy it for a 1.00 s reference onset?
    • Yes; the onset error is 150 ms
    • No; the error is 1.15 s
    • No; every predicted onset must be numerically identical
    • Yes; onset errors are never evaluated
  8. In the heterogeneous 2024 task, how does the baseline handle outputs for classes whose annotations are missing in a training dataset?
    • Treats every unannotated class as certainly absent
    • Copies all missing labels from the final test answers
    • Masks those unavailable outputs in the relevant loss computation
    • Eliminates every labeled class from the model