The article describes the creation of Hidden Markov Model based speech models for both male and female voice for Estonian text-to-speech synthesis. A brief overview of text-to-speech synthesis process is given, focusing on statistical parametric synthesis in particular. System HTS is employed to generate voice models. The creation of speech corpus of Institute of the Estonian Language is analyzed. The process of adapting Estonian-related training data and linguistic specification to HTS is described, as well as experiments carried out on data from different speakers, subcorpora and linguistic specifications. The findings from speech model evaluation are given and possible courses of action to improve the quality of HMM-based speech models trained are proposed.