Polyphonic Audio Key Finding Using the Spiral Array CEG Algorithm

Key finding is an integral step in content-based music indexing and retrieval. In this paper, we present an O(n) real-time algorithm for determining key from polyphonic audio. We use the standard Fast Fourier Transform with a local maximum detection scheme to extract pitches and pitch strengths from polyphonic audio. Next, we use Chew's Spiral Array Center of Effect Generator (CEG) algorithm to determine the key from pitch strength information. We test the proposed system using Mozart's Symphonies. The test data is audio generated from MIDI source. The algorithm achieves a maximum correct key recognition rate of 96% within the first fifteen seconds, and exceeds 90% within the first three seconds. Starting from the extracted pitch strength information, we compare the CEG algorithm's performance to the classic Krumhansl-Schmuckler (K-S) probe tone profile method and Temperley's modified version of the K-S method. Correct key recognition rates for the K-S and modified K-S methods remain under 50% in the first three seconds, with maximum values of 80% and 87% respectively within the first fifteen seconds for the same test set. The CEG method consistently scores higher throughout the fifteen-second selections.