Speech synthesis systems are concerned with generating a natural sounding and intelligiblernspeech by taking text as input. Speech synthesizers are very essential in helping impairedrnpeople, in teaching and learning process, for telecommunications and industries.rnNevertheless, it has been a lot of challenging such as text processing, grapheme to phonemernand modeling prosody for years. Text preprocessing includes tokenization and normalizationrnand then converting the grapheme representation of sounds to their phonetic representationrnand modeling prosodic features of various speaking styles. To address these challenges,rndifferent techniques have been studied and implemented. Speech synthesizers using statisticalrnparametric speech based on hidden Markov model (HMM) are done for foreign languagesrnwhich are not applicable for Afaan Oromoo language since the Afaan Oromoo languageâ€™srnspecial characteristics are not considered in foreign synthesizers. Statistical parametric speechrnsynthesis based on HMM techniques is chosen for these research because it is a model basedrnthat require less storage, it learn properties of data rather store the speech, small run time, andrneasy to integrate with small handheld devices. The Afaan Oromoo text to speech synthesisrnsystem has been developed using statistical parametric speech synthesis based on a hiddenrnMarkov model. The synthesizer has two main components: training and testing phases. In therntraining phase, source and excitation parameters of the speech are extracted from speechrndatabase. The speech and phonetic transcriptions are automatically segmented using EHMMrnlabeling. During testing phase, the input text is processed to form phonetic strings along withrnthe trained models. Finally, the synthesized speech is generated from speech parameters. Inrnorder to train the system being developed, we collected four hundred sentences and speeches.rnAdditionally, we used ten sentences to test the performance of the system. In this study, thernsubjective Mean Opinion Score (MOS) and objective Mel Cepstral Distortion (MCD)rnevaluation techniques are used. The subjective results obtained using the mean opinion scorern(MOS) is 4.3 and 4.1 in terms of the intelligibility and naturalness of the synthesized speechrnrespectively. The objective result obtained using mean opinion score is 6.8 out of 8 which isrnencouraging.