This dissertation presents work done on the development of the speech recognition and the speech synthesis system for Croatian language. Context dependent models of both systems use context dependent hidden Markov models triphones. The use of the same formalism enables a common approach to the development of acoustic models of the systems. Context dependent acoustic models are constructed using the Croatian speech corpus VEPRAD. State tying of the context dependent models is performed using 83 proposed Croatian phonetic rules. A bigram language model is used in the speech recognition system. The Croatian speech corpus VEPRAD was recorded, transcribed and annotated from the radio weather forecast and news broadcasted on the national radio. The speech corpus contains 19 hours of speech spoken by 37 professional speakers and meteorologists. Over 235000 words are included in the corpus, 10000 of which are different words. The VEPRAD corpus comprises over 12000 spoken utterances and their word level transcriptions. The weather reports spoken by meteorologists over the telephone are also included in the corpus. The Croatian speech recognition system was constructed for different domains of interest: the weather forecast and news reports. The achieved speech recognition results for the limited weather domain speech are 96% correctness and 90% accuracy for the clean radio speech with 1462 different words and 96% correctness and 90% accuracy for the noisy telephone speech with 1788 different words. The HMM speech synthesis system was evaluated by 21 evaluators and by speech recognition system. The evaluators mean opinion score is used as the overall quality measure of the generated speech. The correctness and the accuracy of the synthesized speech are given by the speech recognition system. Objective and subjective evaluation results of the synthesized speech are satisfactory and they point that some improvement in the prosodic features should be considered. Achieved multispeaker speech recognition results and speech synthesis results are encouraging for further development of Croatian spoken dialog systems.