Rapid bootstrapping of a Ukrainian large vocabulary continuous speech recognition system

We report on our efforts toward an LVCSR system for the Slavic language Ukrainian. We describe the Ukrainian text and speech database recently collected as a part of our GlobalPhone corpus [1] with our Rapid Language Adaptation Toolkit [2]. The data was complemented by a large collection of text data crawled from various Ukrainian websites. For the production of the pronunciation dictionary, we investigate strategies using grapheme-to-phoneme (g2p) models derived from existing dictionaries of other languages, thereby reducing severely the necessary manual effort. Russian and Bulgarian g2p models even decrease the number of pronunciation rules to one fifth. We achieve significant improvement by applying state-of-the art techniques for acoustic modeling and our day-wise text collection and language model interpolation strategy [3]. Our best system achieves a word error rate of 11.21% on the test set on read newspaper speech.