Abstract
Decision theory is one of the most basic underlying theories which is crucial for the creation, understanding and implementation of a successful speaker recognition algorithm. To begin covering this topic, we need to understand the process of formalizing a hypothesis and testing it. Then, we will continue to talk about Bayesian decision theory. We also talk about hypotheses in the development of information theoretic concepts of Chapter 7.
Keywords
- Equivalence Class
- Ground Truth
- Discriminant Function
- Decision Theory
- Speaker Recognition
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2011 Springer Science+Business Media, LLC
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Beigi, H. (2011). Decision Theory. In: Fundamentals of Speaker Recognition. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77592-0_9
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DOI: https://doi.org/10.1007/978-0-387-77592-0_9
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Publisher Name: Springer, Boston, MA
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Online ISBN: 978-0-387-77592-0
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