  This paper presents text normalization which is an integral part of any
text-to-speech synthesis system. Text normalization is a set of methods with a
task to write non-standard words, like numbers, dates, times, abbreviations,
acronyms and the most common symbols, in their full expanded form are
presented. The whole taxonomy for classification of non-standard words in
Croatian language together with rule-based normalization methods combined with
a lookup dictionary are proposed. Achieved token rate for normalization of
Croatian texts is 95%, where 80% of expanded words are in correct morphological
form.
