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Speech and Speaker Recognition

EESC 6366

Erik Jonsson School of Engineering and Computer Science

Introduction to concepts in automatic recognition methods for speech applications; the primary emphasis is for automatic speech recognition and speaker identification techniques. Topics include speech features for recognition, hidden Markov models (HMMs) for acoustic and language applications (speech recognition, dialect/language recognition), Gaussian mixture models (GMMs) for speaker characterization, robustness issues to address noise and channel conditions for automatic recognition. 3 credit hours.

Offering Frequency: Each year

Grades: 63

Median GPA: A-

Mean GPA: 3.450

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