Automatic Assessment of Student Music Performances

by Alexander Lerch, Georgia Institute of Technology

Abstract

While there is large interest in Music Information Retrieval tasks focusing on extracting score-like information such as pitches, chords, and rhythmic properties, less attention is being paid to performance information such as (micro-)tempo, intonation, and dynamics.
This presentation will look at Music Performance Analysis from the perspective of assessing student music performances. The possibilities and limitations of current data-driven approaches to the assessment of middle and high school students will be discussed based on real-world results on a large dataset of graded student recordings.

Biography

Alexander Lerch is Assistant Professor at the Georgia Tech Center for Music Technology, where he leads the music informatics group. He is working on new artificially intelligent technologies for accessing, producing, and listening to music. His main research field is called Music Information Retrieval (MIR), an emerging interdisciplinary field. He is Co-Founder of the company zplane.development, a research-driven technology provider for the music industry. His book “An Introduction to Audio Content Analysis,” published by Wiley/IEEE Press, is used as course text book in multiple institutions.

More: https://www.alexanderlerch.com/