We introduce in this paper a generalization of the widely used hidden Markov models (HMM's), which we name "structural hidden Markov models" (SHMM). Our approach is ...
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov model...
Illia Horenko, Johannes Schmidt-Ehrenberg, Christo...
In this paper, we propose a general two-dimensional hidden Markov model (2D-HMM), where dependency of the state transition probability on any state is allowed as long as causality...
This paper concentrates on speech duration distributions that are usually invariant to noises and proposes a noise-robust and real-time voice activity detector (VAD) using the hid...
Xianglong Liu, Yuan Liang, Yihua Lou, He Li, Baoso...