Finnish pronunciations being written down phonetically. There are often several ways to write the same word depending on how colloquial the writing style is. Phonological processes such as reductions (“miksi” $\rightarrow$ “miks” \[*why*\]) and even word-internal sandhi (“menenpä” $\rightarrow$ “menempä” \[*I will go*\]) are often visible in written form. Intuitively grouping these different phonetic representations of the same word together would provide a good clustering. While the extent to which a text is colloquial does provide some clues for predicting the next word, in many cases these word forms serve exactly the same function.

This is closely related to normalization of imperfect text, a task which is common in all areas of language technology. Traditionally text normalization is based on hand-crafted rules and lookup tables. In the case that annotated data is available, supervised methods can be used for example to expand abbreviations [@Sproat:2001]. When annotations are not available, candidate expansions for a non-standard word can be found by comparing its lexical or phonemic form to standard words [@Han:2011]. The correct expansion often depends on the context. A language model can be incorporated to disambiguate between the alternative candidates when normalizing text. We are aware of one earlier work where 