Reading acquisition primarily relies on orthographic learning. Behavioral studies show that familiarity with a novel word's pronunciation facilitates learning, particularly in semantically meaningful contexts. Two main components of orthographic learning are commonly described: perceptual processing of the visual stimulus, to infer corresponding phonological representations, and "pronunciation correction", to correct errors from perceptual processing. Currently, pronunciation correction has not been featured in reading acquisition computational models. This study uses BRAID-Acq, a reading acquisition model, to implement and compare two pronunciation correction mechanisms (an "online" and a "post-processing" variant). We simulated learning of words with and without prior phonological knowledge and explored the impact of context strength and size on learning. Results indicate that both mechanisms improve decoding. However, the post-processing mechanism induced implausible lexicalization for words without prior phonological knowledge, while the online mechanism did not. Overall, our simulation results suggest that pronunciation correction could be construed as an online process.