| Instructor | Hao-Wen Dong (ude.hcimu@gnodwh) |
| Room | Moore 376 (Davis) or Zoom |
| Days & times | 1:30–3pm, Mondays & Wednesdays |
| Office hours | By appointment |
[Gradescope] [Last year’s course website]
An introduction to the emerging field of AI music. This course introduces students to AI’s applications in music from analysis, creation, retrieval to processing. Example topics include music transcription, optical music recognition, music source separation, automatic music composition, music synthesis, music recommendation and auto-mixing. Students will gain hands-on experience on using AI tools through open-ended assignments and a final project on a relevant topic of their choice. Prior coding experience is recommended.
| Week | Date | Lecture | Recording | Assignment |
|---|---|---|---|---|
| 1 | Aug 25 | Introduction | ||
| Background | ||||
| Aug 27 | ├ AI & ML Fundamentals | |||
| 2 | ├ |
|||
| Sep 3 | ├ AI & Music | |||
| 3 | Sep 8 | ├ Music Processing Fundamentals & PA 1 Walkthrough | HW 1 due | |
| Sep 10 | ├ Audio Processing Fundamentals & PA 2 Walkthrough | |||
| 4 | Sep 15 | ├ Deep Learning Fundamentals | PA 1 due | |
| Sep 17 | └ Deep Learning Fundamentals II | |||
| 5 | ||||
| Analysis | ||||
| 6 | Sep 29 | ├ Music Analysis | PA 2 due | |
| Oct 1 | ├ Convolutional Neural Networks | |||
| 7 | Oct 6 | ├ Source Separation & PA 3 Walkthrough | HW 2 due | |
| Oct 8 | ├ Deep learning fundamentals III | |||
| 8 | ├ |
|||
| Oct 15 | └ Music Classification & PA 4 Walkthrough | |||
| 9 | Oct 20 | Buffer | PA 3 due | |
| Creation | ||||
| Oct 22 | ├ Language-based Music Generation | |||
| 10 | Oct 27 | ├ Pianoroll-based Music Generation | HW 3 due | |
| Oct 29 | ├ Audio-domain Music Generation | |||
| 11 | Nov 3 | └ Latent-based Music Generation | PA 4 due | |
| Nov 5 | Project pitch | |||
| Retrieval & Processing | ||||
| 12 | Nov 10 | ├ Music Search & Recommendation | ||
| Nov 12 | └ Music Production & Editing | |||
| 13 | Nov 17 | Buffer | HW 4 due | |
| Nov 19 | Discussion | |||
| 14 | Nov 24 | Discussion | ||
| 15 | Dec 1 | Final Presentation | ||
| 16 |
| Assignment | Content | Due |
|---|---|---|
| HW 1 | Real or Fake!? | Sep 8 |
| HW 2 | Stem Separation & Beat Tracking | TBD |
| HW 3 | Music Generation | TBD |
| HW 4 | AI Song Contest | TBD |
| PA 1 | Symbolic Music Processing | TBD |
| PA 2 | Spectral Analysis | TBD |
| PA 3 | Source Separation | TBD |
| PA 4 | Musical Note Classification | TBD |
| Milestone | Due |
|---|---|
| Group forming | Oct 27 |
| Pitch | Nov 5 |
| Video presentation | Dec 15 |
| Report | Dec 15 |
All grading and regrade requests will be handled on Gradescope.
The final grading scale is as follows.
| A+ | >96 | B+ | 87–89 | C+ | 77–79 | D+ | 67–69 | F | <60 |
| A | 93–96 | B | 83–86 | C | 73–76 | D | 63–66 | ||
| A− | 90–92 | B− | 80–82 | C− | 70–72 | D− | 60–62 |
The University of Michigan recognizes disability as an integral part of diversity and is committed to creating an inclusive and equitable educational environment for students with disabilities. Students who are experiencing a disability-related barrier should contact Services for Students with Disabilities ((734) 763-3000 or ssdoffice@umich.edu). For students who are connected with SSD, accommodation requests can be made in Accommodate. If you have any questions or concerns please contact your SSD Coordinator or visit SSD’s Current Student webpage. SSD considers aspects of the course design, course learning objects and the individual academic and course barriers experienced by the student. Further conversation with SSD, instructors, and the student may be warranted to ensure an accessible course experience.
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