A key challenge in sonic interaction design is the lack of a shared vocabulary for describing sound in ways non-experts can easily understand. To address this, we investigate the intuitive use of a lexicon originally developed for communication between sound designers and stakeholders. Building on a pre-study with pre-labeled stimuli, this new study tests the descriptors with a larger, unlabeled dataset. Through online listening tests, participants categorized sounds using selected descriptors, and their responses were compared to expert labels. Our findings confirm that descriptors such as Rough, Smooth, Metallic are the most intuitively well understood; Dull, Warm, Round and Non Round are also relatively well understood. These results inform ongoing research on sound preferences and the development of tools for personalized sonic interactions, helping listeners articulate their preferences for user-centered sonic interactions.