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The text-to-speech (TTS) synthesis technology enables machine to convert text into audible speech and used throughout the world to enhance the accessibility of the information. The important component of any TTS synthesis system is the database of sounds. In this study, three types of sound units i.e., phonemes, diphones and syllables are concatenated to produce natural sound for good quality Sindhi text to speech (STTS) system. The object of this paper consists in treating the phonemes, diphones and syllables under the aspect of the lexicon. The methodology used in STTS is to exploit acoustic representations of speech for synthesis, together with linguistic analyses of text. Sindhi is highly homographic language, the text is written without diacritics in real life applications, that creates lexical and morphological ambiguity. The problem of understating non-diacritic words can be solved using semantic knowledge. This paper describes a Sindhi TTS synthesis system that relies on a WordNet to identify the analogical relations between words in the text. The proposed approach is focused on the use of WordNet structures for the task of synthesis. The architecture and novel algorithm for STTS is proposed. The experiments using WordNet that show promising results and the accuracy of our proposed approach is acceptable.