understandable transcripts. Recognizing a suffix correctly can also help to predict the other words in the sentence. By collecting enough training data, we can get a good coverage of the words in one form or another—perhaps names and numbers being an exception—but we are far from having enough training data to find examples of all the inflected word forms.

Another common feature of Finnish and Estonian is that the orthography is phonemic. Consequently, the spelling of a word can be altered according to the pronunciation changes in conversational language. Especially Finnish conversations are written down preserving the variation that happens in colloquial pronunciation [@Enarvi:2013]. Modeling such languages as a sequence of complete word forms becomes difficult, as most of the forms are very rare. In our data sets, most of the word forms appear only once in the training data.

Agglutination has a far more limited impact on the vocabulary size in English. Nevertheless, the vocabularies used in English language have grown as larger corpora are used and computers are able to store larger language models in memory. Moreover, as speech technology improves, we start to demand better recognition of e.g. proper names that do not appear in the training 