Role of HMM in speech recognition [duplicate]

1. Why HMM is used in speech recognition?
2. What is HMM in pattern recognition?
3. What are HMMs used for?
4. How Hidden Markov model is used in face recognition?

Why HMM is used in speech recognition?

Hidden Markov model (HMM) is the base of a set of successful techniques for acoustic modeling in speech recognition systems. The main reasons for this success are due to this model's analytic ability in the speech phenomenon and its accuracy in practical speech recognition systems.

What is HMM in pattern recognition?

Hidden Markov models (HMMs) are frequently implemented for gesture recognition. From: Encyclopedia of Biomedical Engineering, 2019.

What are HMMs used for?

A hidden Markov model (HMM) is a statistical model that can be used to describe the evolution of observable events that depend on internal factors, which are not directly observable. We call the observed event a `symbol' and the invisible factor underlying the observation a `state'.

How Hidden Markov model is used in face recognition?

For face detection, a set of face images is used in the training of one HMM. The images in the training set represent frontal faces of different people taken under different illumination conditions. For face recognition, each individual in the database is represented by an HMM face model.