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With the increasing deployment of voice-controlled devices in homes and enterprises, there is an urgent demand for voice identification to prevent unauthorized access to sensitive information and property loss. However, due to the broadcast nature of sound wave, a voice-only system is vulnerable to adverse conditions and malicious attacks. We observe that the cooperation of millimeter waves (mmWave) and voice signals can significantly improve the effectiveness and security of user identification. Based on the properties, we propose a multi-modal user identification system (named WavoID) by fusing the uniqueness of mmWave-sensed vocal vibration and mic-recorded voice of users. To estimate fine-grained waveforms, WavoID splits signals and adaptively combines useful decomposed signals according to correlative contents in both mmWave and voice. An elaborated anti-spoofing module in WavoID …