AES E-Library

AES E-Library

Objective Descriptors for the Assessment of Student Music Performances

Assessment of students' music performances is a subjective task that requires the judgment of technical correctness as well as aesthetic properties. A computational model that automatically evaluates music performance based on objective measurements is often desirable to ensure the consistency and reproducibility of these assessments, e.g., for automatic music tutoring systems. In this study, we investigate the effectiveness of various audio descriptors for assessing students’ performances. Specifically, three different sets of features, including a baseline set, score-independent features, and score-based features, are compared with respect to their efficiency in regression tasks. The results show human assessments can be modeled to a certain degree, however, the generality of the model still needs further investigation.

AES Conference:
Paper Number:
Publication Date:

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:

Start a discussion about this paper!

AES - Audio Engineering Society