Smooth ergodic hidden Markov model and its applications in text to speech systems

In text-to-speech systems, the accuracy of information extraction from text is crucial in producing high quality synthesized speech. In this paper, a new scheme for converting text into its equivalent phonetic spelling is proposed and developed. This method has many advantages over its predecessors and it can complement many other text to speech converting systems in order to get improved performance.