In traditional, generative phonology, sound patterns are represented in terms of abstract features, typically based on the articulatory properties of the sounds. The present study makes use of an artificial language learning experiment to explore when and how learners extend a novel phonological pattern to novel segments. Adult, English-speaking learners were exposed to a spirantization pattern in which a stop became a fricative between two vowels (e.g., /bib/ + /o/ [right arrow] [bivo]). Participants were trained on spirantization for two of four possible stop-fricative pairs, and were tested on their generalization to the held-out segments. Two groups of participants were trained on items based on voicing (e.g., the Voiced condition was trained on /b/ [right arrow] [v], and /d/ [right arrow] [z], and tested on /p/ [right arrow] [f], and /t/ [right arrow] [s]), and two groups of participants were trained on items based on place of articulation (e.g., the Labial condition was trained on /b/ [right arrow] [v], and /p/ [right arrow] [f] and tested on /t/ [right arrow] [s], and /d/ [right arrow] [z]). Participants in both Place and Voice conditions were successful at learning and generalizing the spirantization pattern to novel segments, but rates of generalization were higher in the Voice conditions. These results support a similarity-based approach to generalization, particularly one that takes into account articulatorily-based features and natural classes. Implications for phonological theory are discussed.