Learning a second language (L2) is challenging partly due to perceptual strategies inherited from learners’ first language. For example, speakers of tone languages like Mandarin over-use pitch in English prosody perception and production. We developed a novel training paradigm to help Mandarin learners adopt more native-like strategies by enhancing their use of duration relative to pitch cues during prosody categorization. After prosody training, participants used duration more during phrase boundary categorization but showed no clear change for contrastive focus and lexical stress, suggesting that cue weighting training is most effective when targeting a feature’s primary cue. The control group, who practiced English vocabulary, relied more on pitch in lexical stress categorization and phrase boundary production after training, suggesting that without targeted instruction, listeners default to existing strategies. Our findings demonstrate that although default strategies in L2 speech perception are difficult to resist, lifelong perceptual habits can be adjusted with training.

This methodological study investigated how the distribution of training sessions—massed, equal spacing, and expanding spacing—affects L2 phonetic learning, focusing on Mandarin-speaking learners’ perception of the English /ɛ/–/æ/ contrast. While most previous phonetic training studies have used massed schedules, the current quasi-experimental design revealed that both types of spaced practice significantly outperformed massed practice in terms of immediate gains and long-term retention. Effect sizes in the spaced groups were approximately double those of the massed group. No significant differences emerged between equal and expanding spacing. These findings suggest that distributed practice—regardless of spacing type—can enhance both the magnitude and durability of L2 phonetic learning. Crucially, this study makes it possible to revisit past findings based on massed training paradigms and to consider whether adopting alternative timing schedules could unlock greater learning potential—for instance, by doubling the size and durability of training effects through the use of spaced conditions.