Implementation and evaluation of statistical parametric speech synthesis methods for the Persian language
Sara Bahaadini, Hossein Sameti, Soheil Khorram · 2011
Scattered and little research in the field of Persian speech synthesis systems has been performed during the last ten years. Comprehensive framework that properly implements and adapts statistical speech synthesis methods for Persian has not been conducted yet. In this paper, recent statistical parametric speech synthesis methods including CLUSTERGEN, traditional HMM-based speech synthesis and its STRAIGHT version, are implemented and adapted for Persian language. CCR test is carried out to compare these methods with each other and with unit selection method. Listeners Score samples based on CMOS. The methods were ranked by averaging the CCR scores. The results show that STRAIGHT-based system produces the best quality. Traditional HMM-based and unit selection are second and third in quality ranking. These approximately produce the same quality. Finally CLUSTERGEN produces the worst quality among these four systems.