Computational accounts of reading aloud largely ignore context when stipulating how processing unfolds. One exception to this state of affairs proposes adjusting the breadth of lexical knowledge in such models in response to differing contexts. Three experiments and corresponding simulations, using Coltheart, Rastle, Perry, Langdon, and Ziegler's (2001) dual-route cascaded model, are reported. This work investigates a determinant of when a pseudohomophone such as brane is affected by the frequency of the word from which it is derived (e. g., the base word frequency of brain) by examining performance under conditions where it is read aloud faster than a nonword control such as frane. Reynolds and Besner's (2005a) lexical breadth account makes the novel prediction that when a pseudohomophone advantage is seen, there will also be a base word frequency effect, provided exception words are also present. This prediction was confirmed. Five other accounts of this pattern of results are considered and found wanting. It is concluded that the lexical breadth account provides the most parsimonious account to date of these and related findings.