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Sensing movements and gestures inside the oral cavity has been a long-standing challenge for the wearable research community. This paper introduces EchoNose, a novel nose interface that explores a unique sensing approach to recognize gestures related to mouth, breathing, and tongue by analyzing the acoustic signal reflections inside the nasal and oral cavities. The interface incorporates a speaker and a microphone placed at the nostrils, emitting inaudible acoustic signals and capturing the corresponding reflections. These received signals were processed using a customized data processing and machine learning pipeline, enabling the distinction of 16 gestures involving speech, tongue, and breathing. A user study with 10 participants demonstrates that EchoNose achieves an average accuracy of 93.7% in recognizing these 16 gestures. Based on these promising results, we discuss the potential opportunities and challenges associated with applying this innovative nose interface in various future applications.