This paper presents recent improvements on ARTIC -the modern Czech corpus-based text-to-speech system. As a statistical approach (using hidden Markov models) was applied to create an acoustic unit inventory, several improvements concerning acoustic unit modelling, clustering and segmentation have been accomplished to increase the intelligibility of the resulting speech. Two approaches to the generation of prosodic features were also proposed and implemented to increase the naturalness of synthetic speech. To produce as smooth synthetic speech as possible, a multiple unit instance scheme with on-line unit candidate selection was proposed as well. Our work on an alternative harmonic/noise-based speech production method is also mentioned. In addition, an important step towards multilinguality was achieved as German and Slovak language modules were implemented besides two Czech voices within the framework of ARTIC TTS system.