Most of us are aware of the fact that voices of different individuals do not sound alike. This important property of speech being speaker dependent is what enables us to recognize a friend over a telephone. The ability of recognizing a person solely from his voice is known as speaker recognition. Applications of speaker recognition are becoming ubiquitous, especially after the increased terrorist activities around the world. Speech patterns can prove extremely useful in criminal investigation and litigation. Moreover speaker recognition can be useful to adapt the machines into their users because a speech interface, in a user's own language is ideal as it is the most natural, flexible, efficient, and economical form of human communication. Speaker recognition can be a useful tool in many other areas such as forensic speech analysis. The choice of features plays an important role in the performance of recognizer. Here we propose prosodic feature set for text dependent speaker recognition. Further we propose the use of Machine Learning (ML) algorithms as classifier to overcome the drawbacks of traditional classifiers.
Product Identifiers
Publisher
Lap Lambert Academic Publishing
ISBN-13
9783659396434
eBay Product ID (ePID)
213801621
Product Key Features
Author
Shruti Gujral
Publication Name
Text Dependent Speaker Recognition: a Machine Learning Approach
Format
Paperback
Language
English
Subject
Engineering & Technology
Publication Year
2013
Type
Textbook
Number of Pages
72 Pages
Dimensions
Item Height
229mm
Item Width
152mm
Item Weight
118g
Additional Product Features
Title_Author
Shruti Gujral
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