We propose a model-driven method for ensuring the quality of pronunciation dictionaries. The key ingredient is computing an alignment between letter strings and phoneme strings, a standard technique in pronunciation modeling. The novel aspect of our method is the use of informative, parametric alignment models which are refined iteratively as they are tested against the data. We discuss the use of alignment failures as a signal for detecting and correcting problematic dictionary entries. We illustrate this method using an existing pronunciation dictionary for Icelandic. Our method is completely general and has been applied in the construction of pronunciation dictionaries for commercially deployed speech recognition systems in several languages.