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Course Description

This course covers the basic principles of digital speech processing, including: automatic speech recognition; speech production and perception; pattern recognition; linear and non-linear classifiers; signal processing approaches and methods; pattern recognition applied to ASR; time alignment and normalization; dynamic time warping; Hidden Markov Model (HMM) fundamentals; speech system design; connected word models; dynamic programming; large vocabulary speech recognition; and flexible speech understanding. Every student will bring a laptop with WiFi to each class.

Sample Course Outline

Sample Classroom Course Outline
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