Hidden Markov models (HMMs) and their extensions are attractive methods for analysing ecological data where noisy, multivariate measurements made of a hidden, process, this hidden process is represented by sequence discrete states. Yet, as these become more complex challenging to understand, it important consider what pitfalls have opportunities there future research address pitfalls. In paper,...

Hidden Markov models play a critical role in the modelling and problem solving of important AI tasks such as speech recognition and natural language processing. However, the students often have difficulty in understanding the essence and applications of Hidden Markov models in the context of a cursory introductory coverage of the subject. In this paper, we describe an empirical approach to expl...