Auditory signal processing and perception

• Describe and apply fundamental signal analysis concepts (e.g., convolution, correlation, Fourier transform, sampling, quantization, and aliasing).
• Categorize different types of hearing impairments and their perceptual consequences, and evaluate potential compensation strategies in modern hearing aids and cochlear implants.
• Interpret the principles of signal detection theory and explain their implications for psychophysical measurement methods.
• Analyze sound processing in the inner ear (cochlea) and predict key features of cochlear transformation using electrical circuit modeling.
• Characterize the frequency-selective properties of the auditory system, demonstrate the principles of masking, and evaluate models of auditory masking.
• Explain the temporal processing properties of the auditory system, calculate the modulation spectrum of a stimulus, and evaluate the concept of modulation-frequency–selective processing.
• Discuss methods for measuring loudness and intensity discrimination, and evaluate models of loudness perception and intensity coding in the auditory system.
• Demonstrate and explain the principles of spatial and binaural hearing, and predict binaural perception outcomes using an equalization–cancellation model.
• Relate speech intelligibility performance to stimulus characteristics, room acoustics, and hearing status, and compare and evaluate different methods for measuring speech intelligibility.
• Discuss models of signal processing in auditory neurons and evaluate physiologically inspired models of auditory perception.
• explain methods for measuring otoacoustic emissions and acoustically evoked brain potentials; categorize different types of evoked potentials; interpret the role of cochlear processing for the generation of brainstem potentials
• Critically evaluate machine-learning–based models of auditory signal processing and perception, including their capabilities, limitations, and potential applications in diagnostics and hearing-loss compensation.

Psychophysics and physiology of the auditory system. Models of auditory signal processing and perception. Neurophysiological measurement methods and their relation to psychoacoustical (behavioral) findings. Neural imaging techniques. Technical and clinical applications, including compensation strategies in modern hearing aids and cochlear implants. The course also introduces computational and machine-learning–based modeling approaches for analyzing auditory data and predicting perceptual outcomes. Classroom-based problem-solving sessions and seven MATLAB-based exercises complement selected lectures throughout the course.

Lectures and exercises.

E-learning is incorporated through online interactive quizzes, recorded video lectures, a course wiki open to student contributions, discussion boards or blogs, web-based tools, and a digital whiteboard. Students who plan to take 22006 Acoustic Communication are advised to complete that course before enrolling in this course.