EECS 225d (3 units)
Audio Signal Processing in Humans and Machines
Professor Morgan

The focus of the course is on engineering models for speech and music processing. These models are used to design systems for analysis, synthesis, and recognition. For each of these topics there will also be material on physiological and psychoacoustic properties of the human auditory and speech generation systems, particularly from an engineer's perspective: how can we make use of knowledge about these natural systems when we design artificial ones?

Topics include: an introduction to pattern recognition; speech coding, synthesis, and recognition; models of speech and music production and perception; signal processing for speech analysis; pitch perception and auditory spectral analysis with applications to speech and music; a historical survey of speech synthesizers from the 18th century to the present; robustness to environmental variation in speech recognizers; vocoders and music synthesizers; statistical speech recognition, including introduction to Hidden Markov Model and Neural Network approaches.

Prerequisites: EE123 or equivalent, and Stat 200A or equivalent; or grad standing and consent of instructor

Text: Gold and Morgan, Speech and Audio Signal Processing, Wiley Press.