Open For Enrollment

Would you like to enroll?

Enrollment for this course has closed. But you can enroll in a future offering (please select)

Enrollment has closed

Enrollment for this course is currently closed, but the next offering will be available shortly. Check back soon!

Length
5 Sessions
Price
Audit (Free)
Certificate (Incl. w/ Premium)
Credit Eligible Program ($900 USD)
Institution
University of Victoria
Subject
Music, Creative Computing, Music Technology
Skill Level
Expert
Topics
Music, Machine Learning, Music Information Retrieval, Audio Signal Processing, Feature Extraction
Course Description

The course introduces audio signal processing concepts motivated by examples from MIR research. More specifically students will learn about spectral analysis and time-frequency representations in general, monophonic pitch estimation, audio feature extraction, beat tracking, and tempo estimation.

schedule

This course is in scheduled mode and starts Early 2018. Learn more about scheduled courses here.

Session 1: Overview and Introduction to DSP
In this session, we will cover Phasors, Sinusoids, and Complex Numbers.
Session 2: Time-Frequency Representations
In This session, we will learn about Sampling, Quantization, RMS, and Loudness. We will also cover DFT, Hilbert Spaces, and Spectrograms.
Session 3: Monophonic pitch analysis/autocorrelation
Pitch vs Fundamental Frequency, Time-domain, Frequency-domain, Perceptual Models, Overview of applications (Query-by-Humming, Auto-tunining) will be covered in this session.
Session 4: Audio feature extraction
We will go over Spectral Features, Mel-Frequency Cepstral Coefficients, temporal aggregation, chroma and pitch profiles.
Session 5: Rhythm Analysis
This session is about Tempo estimation, beat tracking, drum transcription, pattern detection.
Enroll for College Credit

Credit Eligible

Kadenze has partnered with University of Victoria to offer this program for 3.0 college credits.*

How much does it cost?

This course costs $900 USD to take for college credit.

*Upon completion, this rigorous college-level program will provide credits that are recognized and transferable from the partnering institution. Credit as workload and transferability is defined by the granting institution. Participation in these courses does not represent an acceptance decision or admission from the institution that offers them.

Learning Outcomes

Below you will find an overview of the Learning Outcomes you will achieve as you complete this course.

Certificates
Whenever you complete a course as a premium member, you can earn a verified Certificate of Accomplishment .

This course is also part of the Program: Music Information Retrieval . Earn a verified Specialist Certificate for successfully completing a Program.

These certificates are proof that you completed an online course on our platform and can easily be shared with its unique link.

Credit Elligible Program
This course is one of 3 courses in the Music Information Retrieval Program and is offered for credits from University of Victoria.

Earn a verified Specialist Certificate after successfully completing a Program. And whenever you complete a course as a Premium member, you earn a verified Certificate of Accomplishment . These certificates are proof that you completed an online course on our platform and can easily be shared with its unique link.

Instructors & 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.
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 the institution offering this course.

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.

Peer Assessment Code of Conduct: Part of what makes Kadenze a great place to learn is our community of students. While you are completing your Peer Assessments, we ask that you help us maintain the quality of our community. Please:

  • Be Polite. Show your fellow students courtesy. No one wants to feel attacked - ever. For this reason, insults, condescension, or abuse will not be tolerated.
  • Show Respect. Kadenze is a global community. Our students are from many different cultures and backgrounds. Please be patient, kind, and open-minded when discussing topics such as race, religion, gender, sexual orientation, or other potentially controversial subjects.
  • Post Appropriate Content. We believe that expression is a human right and we would never censor our students. With that in mind, please be sensitive of what you post in a Peer Assessment. Only post content where and when it is appropriate to do so.

Please understand that posts which violate this Code of Conduct harm our community and may be deleted or made invisible to other students by course moderators. Students who repeatedly break these rules may be removed from the course and/or may lose access to Kadenze.

Students with Disabilities: Students who have documented disabilities and who want to request accommodations should refer to the student help article via the Kadenze support center. Kadenze is committed to making sure that our site is accessible to everyone. Configure your accessibility settings in your Kadenze Account Settings.