PREREQUISITE

ARTS 2380 or ARTS 2020, or permission of instructor

COURSE DESCRIPTION

Advances in machine learning and artificially-intelligent systems are currently being applied to creative tasks such as musical composition and performance. This course is an advanced seminar focusing on the current state of AI research and application in musical domains. Topics to be discussed include the ethics of AI's use in music, the way(s) that trained systems are being applied towards the creation and performance of music and the hands-on application of AI/ML toolsets and frameworks for musical expression.

CATALOG DESCRIPTION

This is a course introducing music majors to advanced research topics of the Rensselaer music faculty. Each semester a member of the music faculty will focus the seminar on a research topic or paradigm related to their own body of artistic and technological research. Sample topics might include Spatial music and sound, New Instrument Design, Network Music, Music Information Retrieval, Ethnomusicology, Sonification Art and Science, Music and Logic, Spectralism and Beyond, Music Herstory (feminist music composition), Experimental music and sound history. Through hands-on creative research, students will explore questions of both musical and technological significance while engaging that same topic through their own hands-on creative practice.

LEARNING OUTCOMES

Students who successfully complete this course will demonstrate...
1. an understanding and appreciation of the current statue of AI/ML systems for musical creation
2. basic technical facility in the application of current tools and frameworks for AI/ML assisted composition, source separation, classification, sound synthesis and post production.
3. creativity and resourcefulness through the creation of musical AI/ML systems and creation/composition of their own sonic projects

EVALUATION

Evaluation is based on the following:

• Homework Assignments/Projects (40%)
• In-Class Presentations(20%)
• Attendance/class participation (40%)

CLASS PARTICIPATION

You will be required to present some of your assignments to the class, to show your work within the software environment you used to create it, and to engage the class in discussion of your work. When you are not presenting your own work, you need to be attentive to whoever is presenting, and to engage them in discussion of their work. Failure to participate in class will lower your grade.

ATTENDANCE

You must attend class to succeed in this course.

1. Since much of the class is focused on listening to and discussing work in class, attendance is mandatory.
2. ** More then two unexcused absences will affect your grade, detracting 1/2 grade each additional 2 unexcused absences. **
3. Late arrivals are very disruptive - continued late arrival will affect your grade.
4. It should go without saying but no use of mobile devices or personal computers during class time (except for as required by the coursework itself) is acceptable. Continued violations will be treated as an unexcused absence.

STATEMENT REGARDING ACADEMIC INTEGRITY

Collaboration between students in this course is strongly encouraged. Likewise, students are encouraged—indeed, to some extent required—to exchange ideas, opinions and information . You are also encouraged to help each other in the lab and with performance, production, and presentation of composition projects.

Plagiarism of any kind is in direct violation of University policy on Academic Dishonesty as defined in the Rensselaer Handbook, and penalties for plagiarism can be severe. In this class you will be expected to attribute due credit to the originator of any ideas, words, sounds, or music which you incorporate substantially into your own work. This applies particularly to citation of sources for sonic "samples" included in your compositions.

The use of automated technical aids (e.g. ChatBots, AI code plugins) is not strictly forbidden but if used MUST be documented in great detail and discussed with the Professor prior to use in a graded project/assignment.

Submission of any assignment that is in violation of this policy may result in a grade of F for the assignment in question. Violation of this policy will be reported, as defined in the Rensselaer Handbook

DISABILITY SERVICES FOR STUDENTS

Students requiring assistance are encouraged to contact Disability Services: http://doso.rpi.edu/dss to discuss any special accommodations or needs for this course.

OFFICE HOURS

Office Hours for Spring, 2024 will be TBD

TEXTBOOKS / REPOSITORIES / FOUNDATIONAL MATERIAL