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区分矩阵和区分函数是求核和约简的有力工具。
Discernibility matrix and discernibility function are a powerful tool seeking nuclear attributes and attribute reduction.
如果不是面向特定背景噪声的应用，通过寻找噪声的共同特征以构建一个噪声信号与语音信号的区分函数是不现实的。
If no specific application background is assumed, it's nearly impossible to build a discrimination function to distinguish speech from background noise with current VAD technologies.
这能帮助区分关键字和函数调用。
This helps to distinguish between keywords and function invocations.
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