Synchronized Swept-Sine: Theory, Application, and Implementation - October 2015
Effect of Microphone Number and Positioning on the Average of Frequency Responses in Cinema Calibration - October 2015
The Measurement and Calibration of Sound Reproducing Systems - July 2015
Analyzing Chroma Feature Types for Automated Chord Recognition
The computer-based harmonic analysis of music recordings with the goal to automatically extract chord labels directly from the given audio material constitutes a major task in music information retrieval. In most automated chord recognition procedures, the given music recording is first converted into a sequence of chroma-based audio features and then pattern matching techniques are applied to map the chroma features to chord labels. In this paper, we analyze the role of the feature extraction step within the recognition pipeline of various chord recognition procedures based on template matching strategies and hidden Markov models. In particular, we report on numerous experiments which show how the various procedures depend on the type of the underlying chroma feature as well as on parameters that control temporal and spectral aspects.
Click to purchase paper 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 $20 for non-members, $5 for AES members and is free for E-Library subscribers.