An NLP based text-to-speech synthesizer for Moroccan Arabic

Abstract

The ultimate goal of text-to-speech synthesis is to produce natural sounding speech from any text sequence regardless of its complexity and ambiguity. For this purpose, many approaches combine different models to text-to-speech methods in order to enhance results. Applying text-to-speech to Arabic dialects presents additional challenges, such as ambiguity of undiacritized words, and lack of linguistics resources. In this respect, the purpose of this chapter is to present a text-to-speech synthesizer for Moroccan Arabic based on NLP rule-based and probabilistic models. The chapter contains a presentation of Moroccan Arabic linguistics, an analysis of NLP techniques in general, and Arabic NLP techniques in particular.