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In this paper, we present MuteIt, an ear-worn system for recognizing unvoiced human commands. MuteIt presents an intuitive alternative to voice-based interactions that can be unreliable in noisy environments, disruptive to those around us, and compromise our privacy. We propose a twin-IMU set up to track the user's jaw motion and cancel motion artifacts caused by head and body movements. MuteIt processes jaw motion during word articulation to break each word signal into its constituent syllables, and further each syllable into phonemes (vowels, visemes, and plosives). Recognizing unvoiced commands by only tracking jaw motion is challenging. As a secondary articulator, jaw motion is not distinctive enough for unvoiced speech recognition. MuteIt combines IMU data with the anatomy of jaw movement as well as principles from linguistics, to model the task of word recognition as an estimation problem. Rather …