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However, nonverbal sound has a broad interpretation and design space that can draw from areas such as machine learning, music theory, and foley. We sought to identify and compare use cases and approaches for nonverbal sound in human-robot interaction through a systematic review. A search of sound and robotics-related publisher databases yielded 148 peer-reviewed articles presenting systems, studies, and taxonomies. Differences in taxonomy and overlap of terminology with adjacent research fields such as speech, gaze, and gesture posed difficulties for the search, which we attempted to address through a multi-stage search process. Based on the reviewed articles, we developed a pair of taxonomies using scientific communication principles and analyzed study designs and measures for the creation of nonverbal robot sound. We discuss recommendations for the field, including the use of the new taxonomies; methods for design, generation, and validation; and paths for future research. 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