Latent state recognition by an enhanced hidden Markov model

•The hidden Markov model is extended to relax two primary assumptions.•The observation is modelled as a vector autoregressive process.•The hidden state evolution follows a semi-Markov chain.•The autoregressive and covariance matrices are regularized with penalty.•The proposed model shows a promising performance in latent state recognition.