Estimating The Tonality Of Polyphonic Audio Files: Cognitive Versus Machine Learning Modelling Strategies

In this paper we evaluate two methods for key estimation from polyphonic audio recordings. Our goal is to compare between a strategy using a cognition-inspired model and several machine learning techniques to find a model for tonality (mode and key note) determination of polyphonic music from audio files. Both approaches have as an input a vector of values related to the intensity of each of the pitch classes of a chromatic scale. In this study, both methods are explained and evaluated in a large database of audio recordings of classical pieces.

• Type: Conference
• Year: 2004
• Where: ISMIR
• Authors: Emilia Gómez, Perfecto Herrera
• Keywords: ISMIR 2004, Key Estimation, Machine Learning Techniques, Polyphonic Audio Recordings