A Revised Comparison of Polish Taggers in the Application for Automatic Speech Recognition

In this paper (This is a revised and extended version of the article A Comparison of Polish Taggers in the Application for Automatic Speech Recognition that appeared in the Proceedings of Language and Tools Conference, Poznan, 2013.) we investigate the performance of Polish taggers in the context of automatic speech recognition (ASR). We use a morphosyntactic language model to improve speech recognition in an ASR system and seek the best Polish tagger for our needs. Polish is an inflectional language and an n-gram model using morphosyntactic features, which reduces data sparsity seems to be a good choice. We investigate the difference between the morphosyntactic taggers in that context. We compare the results of tagging with respect to the reduction of word error rate as well as speed of tagging. As it turns out at present the taggers using conditional random fields (CRF) models perform the best in the context of ASR. A broader audience might be also interested in the other discussed features of the taggers such as easiness of installation and usage, which are usually not covered in the papers describing such systems.