Development of Acoustic Model for Croatian Language Using HTK

Paper presents development of the acoustic model for Croatian language for automatic speech recognition (ASR). Continuous speech recognition is performed by means of the Hidden Markov Models (HMM) implemented in the HMM Toolkit (HTK). In order to adjust the HTK to the native language a novel algorithm for Croatian language transcription (CLT) has been developed. It is based on phonetic assimilation rules that are applied within uttered words. Phonetic questions for state tying of different triphone models have also been developed. The automated system for training and evaluation of acoustic models has been developed and integrated with the new graphical user interface (GUI). Targeted applications of this ASR system are stress inoculation training (SIT) and virtual reality exposure therapy (VRET). Adaptability of the model to a closed set of speakers is important for such applications and this paper investigates the applicability of the HTK tool for typical scenarios. Robustness of the tool to a new language was tested in matched conditions by a parallel training of an English model that was used as a baseline. Ten native Croatian speakers participated in experiments. Encouraging results were achieved and reported with the developed model for Croatian language.