Gaussian Mixture Model-UBM based for image recognition

1. What is UBM GMM?
2. Why is GMM used in speech recognition?
3. What is GMM in speech recognition?
4. Is Gaussian mixture model a classification model?

What is UBM GMM?

In GMM-UBM based modelling certain amount of data from all the language classes is pooled to develop a universal background model (UBM) and the model is adapted to each class. Spectral features (MFCC) are employed to represent the language specific phonotactic information of speech in different languages.

Why is GMM used in speech recognition?

GMMs are commonly used as a parametric model of the probability distribution of continuous measurements or features in a biometric system, such as vocal-tract related spectral features in a speaker recognition system.

What is GMM in speech recognition?

Using a statistical model like Gaussian mixture model (GMM) and features extracted from those speech signals we build a unique identity for each person who enrolled for speaker recognition.

Is Gaussian mixture model a classification model?

Gaussian mixture models (GMMs) are a type of machine learning algorithm. They are used to classify data into different categories based on the probability distribution.