Course Description

Computer audition is the study of how to design a computational system that can analyze and process auditory scenes. Problems in this field include source separation (splitting audio mixtures into individual source tracks), pitch estimation (estimating the pitches played by each instrument), streaming (finding which sounds belong to a single event/source), source localization (finding where the sound comes from) and source identification (labeling a sound source).

This course is a graduate course covering current research in the field. The class starts with a brief review of signal processing techniques, then introduces auditory models, audio features, and audio modeling methods. Recent advances in state-of-the-art research topics including multi-pitch analysis, source separation, source localization, instrument identification then follow.

In the first half of the semester, students will finish four homework assignments (Matlab programming) that cover the basics. Students are also required to read ten recently published papers in the field and write reviews about them. In the second half of the semester, each student will present a research paper in class. Students will also finish a final project, including selecting a topic, read several related papers, proposing and implementing their ideas, and writing a report. Students’ presentations and final project reports will be uploaded to the course website for others to look at. Students will give feedbacks to other students’ presentations and final projects.

Course Information

Credits: 4
Lectures: 12:30-1:45PM on Tuesdays and Thursdays
Classroom: Meliora 224
Prerequisites: ECE 246/446 or ECE 272/472 or other equivalent signal processing courses, and Matlab programming. Knowledge of machine learning techniques such as Markov models, support vector machines, and neural networks is also helpful, but not required.
Textbook: No textbook is required. We will read a number of research papers in the field. The following texts are for references and have been put on reserve at UR library. Some excerpts of them will be provided to students.

Instructor: Zhiyao Duan
Office: CSB 720
Email: zhiyao.duan (at)
Office hour: Wednesdays 4-5PM

Teaching Assistant: Yichi Zhang
Office: CSB 504
Email: yichi.zhang (at)
Office hour: Thursdays 2-3PM

Librarian: Moriana Garcia
Office: Carlson 313D
Email: mgarcia (at)
Office hour: Email or visit here
Services: Students are encouraged to consult with our librarian for questions regarding how to find and cite resources, and how to engage more effectively with the research process.