Abstract
The basic objective of speaker modeling is to be able to be able to associate an identifier to the speech of an individual speaker which is different from all other unique speakers, if not in the world, at least in the database of interest. Once this is achieved, all the different branches of speaker recognition, discussed in Chapter 1, may come to fruition. In other words, speaker modeling lies at the heart of the speaker recognition task. This may not necessarily be true with many other seemingly similar fields. For example, speech recognition which is very closely related to speaker recognition requires many different stages, many of which are of similar importance. For instance, in speech recognition, the phonetic modeling, language modeling, and search are almost of similar importance. In speaker recognition, on the other hand, if a good model of the speaker is built, the rest of the work becomes extremely easy.
Keywords
- Gaussian Mixture Model
- Speaker Recognition
- Cohort Model
- Universal Background Model
- Target Speaker
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). Speaker Modeling. In: Fundamentals of Speaker Recognition. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77592-0_16
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DOI: https://doi.org/10.1007/978-0-387-77592-0_16
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