A text-to-speech (TTS) synthesis system converts natural language text into speech. However, written text of a language contains both standard words (SWs) and non-standard words (NSWs) like numbers, abbreviations, synonyms, currency, and dates. These NSWs cannot be detected by an application of “letter-to-sound” rule.This work try to produce Amharic TTS system, which handle both standard words(SWs) and Non-standard words (NSWs) of Amharic language. The model described in this work has two major parts: Natural language processing (NLP) and Digital signal processing (DSP). The NLP handles the text analysis (transcription of the input SWs and NSWs) and extraction of the speech parameters. The DSP further enable to generate the artificial speech. Finally, the performance of the system shows that on the average 73.35% words both SWs and NSWs correctly pronounced. In addition, an assessment of intelligibility and naturalness of synthesized speech using MOS testing techniques results a score of 3 and 2.83, respectively.The experiment shows a promising result to design an applicable system that synthesis both SWs and NSWs for unrestricted text of a language.