A RPCL-Based Approach for Identification of Markov Model with Unknown Noise and Number of States

Hidden Markov Model and Deep Neural Networks based Statistical Parametric Speech Synthesis systems, gain a significant attention from researchers because of their flexibility in generating speech waveforms in diverse voice qualities as well as in ...

A statistical speech synthesis system based on the hidden Markov model (HMM) was recently proposed. In this system, spectrum, excitation, and duration of speech are modeled simultaneously by context-dependent HMMs, and speech parameter vector sequences ...

In the standard hidden Markov model, the current state depends only on the immediately preceding state, but has nothing to do with the immediately preceding observation. This paper presents a new type of hidden Markov models in which the current state ...