This work presents the effectiveness of using machine learning (ML) synthesized voice samples to control smart speaker devices through radiated intentional electromagnetic interference (I-EMI). In previous works, the feasibility of using I-EMI to control smart speaker devices was shown. However, devices that are trained to only recognize a single person's voice or only execute certain commands from that person will not be as susceptible to this attack. By training a generative adversarial network (GAN) using samples of the target's voice, this security feature can be bypassed directly, increasing the feasibility of the attack.