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Starts in 2 hours
You can also start immediately after joining!
This exclusive course is part of the program:
Music Information Retrieval
Go at your own pace
5 Sessions / 10 hours of work per session
Included w/ premium membership ($20/month)
Skill Level
Expert
Video Transcripts
English, Afrikaans
Topics
Music, Music Information Retrieval, Audio Signal Processing
Open for Enrollment

Music Retrieval Systems

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Go at your own pace
5 Sessions / 10 hours of work per session
Included w/ premium membership ($20/month)
Skill Level
Expert
Video Transcripts
English, Afrikaans
Topics
Music, Music Information Retrieval, Audio Signal Processing
Course Description

Course 3 builds upon the digital signal processing concepts we have learned in Course 1 and the machine learning concepts we have learned in Course 2 to investigate a variety of interesting music information retrieval tasks. As these tasks become more advanced and complicated, the examples and assignments in this course shift from programming examples from scratch to utilizing existing libraries and frameworks. Topics explored include: music recommendation and query-by-humming, automatic chord detection and cover song identification, automatic music transcription and sound source separation, and audio fingerprinting and watermarking. By completing the course, you will have a good coverage of all the work that has been done in the field of MIR.

schedule

This course is in adaptive mode and is open for enrollment. Learn more about adaptive courses here.

Session 1: Query Retrieval (September 25, 2021)
In this session, we will cover the basics of audio fingerprinting and watermarking: audio landmark extraction, quantization, jaccard similarity, minhash, locality sensitive hashing.
6 lessons
1. Overview
2. Query by Example, Automatic Playlist Generation
3. Embeddings and Manifold Learning
4. Query-by-Humming and Beat-Boxing
5. Dynamic Programming
6. Summary
Session 2: Polyphonic Alignment and Structure Segmentation (October 2, 2021)
This session will describe the problem of chord detection, a quick introduction to music theory and notation, hidden markov models and other types of probabilistic modeling for chord detection and structure segmentation.
7 lessons
1. Overview
2. Polyphonic Pitch Estimation
3. Audio-Score Alignment
4. Score Following
5. Structure Segmentation
6. Music Aware Audio Editing, VAMP Plugins and Sonic Visualizer
7. Summary
Session 3: Chord Detection and Cover Song Identification (October 9, 2021)
We will learn about the basic architecture of a query-by-humming system, theme extraction, note segmentation and quantization.
7 lessons
1. Overview
2. Beat Synchronous Chroma Features
3. Cover Song Identification
4. Chord Detection
5. Hidden Markov Models
6. Markov Logic Networks
7. Summary
Session 4: Transcription and Sound Source Separation (October 16, 2021)
In this session, we will cover MIDI, symbolic music representations, dynamic programming, self-similarity matrices, polyphonic audio-score alignment.
6 lessons
1. Overview
2. Polyphonic Music Transcription
3. Melody Extraction
4. Predominant Melody Separation
5. Sound Source Separation and Non-negative Matrix Factorization
6. Summary
Session 5: Audio Fingerprinting and Watermarking (October 23, 2021)
Principal component analysis, self-organizing maps, visualization in MIR will be covered in this session.
5 lessons
1. Overview
2. Landmark Detection
3. Jaccard Similarity, Min-Hash and Locality Sensitive Hashing
4. Watermarking
5. Summary
Reviews
Instructors And Guests
What You Need to Take This Course

Prior Knowledge

  • Good knowledge of programming, basic linear algebra, probability, and statistics.

Equipment

  • Computer with installation privileges.

Software

  • The course is mostly software agnostic but existing frameworks for MIR and audio will be used. All software will be freely available and typically also open source. Examples include: Audacity, Marsyas, Sonic Visualizer, and VAMP plugins.

Prerequisite

    • "Extracting Information from Music Signals" & "Machine Learning for Music Information Retrieval" must be completed prior to taking this course.
Additional Information

PLEASE NOTE: Taking part in a Kadenze course as a Premium Member does not affirm that you have been enrolled or accepted for enrollment by University of Victoria.

In order to receive college credit for these program courses, you must successfully complete and pass all 3 courses in this program. If a student signs up for the Music Information Retrieval program, it is recommended that these courses are taken sequentially.

*Partial credit will not be awarded for completion of only one course.

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