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We introduce Ada-Mic, a method for adaptive close-to-mic speech detection that allows for flexible orientation ranges of the smartphone. Our method uses Generalized Cross-Correlation features as an auxiliary spatial signal that implicitly encodes the Direction-of-Arrival of speech signals to the smartphone, disentangling features for distance from those relating to orientation. It is a lightweight module that can be easily integrated into existing close-to-mic speech detectors, adding little to negligible amounts of extra computation. Our results show up to 24% improvement in accuracy over prior works for challenging distances and orientations, and demonstrates strong robustness to background noise. Ada-Mic advances the goal of No-Hot-Word wakening, enabling more natural interactions with users.