The scope of this basics section is to provide a short introduction to a few topics and concepts which are essential for speech recognition.

- Gaussian Mixture Models (GMM)

Based on a usual normal distribution, multivariate normal distributions and then GMMs are explained. - Hidden Markov Models (HMM)

Stochastic processes, Markov models and finally Hidden Markov models are explained. - Expectation Maximization (EM)

An general approach to inference and learning in latent variable models. - Artificial Neural Networks (ANN)

The basic concepts of neural networks are introduced.