An efficient method for polyphonic audio-to-score alignment using onset detection and constant Q transform

This paper proposes an innovative method that aligns a polyphonic audio recording of music to its corresponding symbolic score. In the first step, we perform onset detection and then apply constant Q transform around each onset. A similarity matrix is computed by using a scoring function which evaluates the similarity between notes in the music score and onsets in the audio recording. At last, we use dynamic programming to extract the best alignment path in the similarity matrix. We compared two onset detectors and two note matching methods. Our method is more efficient and has higher precision than the traditional chroma-based DTW method. Our algorithm achieved the best precision, which are 10% higher than the compared traditional algorithm when the tolerance window is 50 ms.