Drum Sound Recognition for Polyphonic Audio Signals by Adaptation and Matching of Spectrogram Templates With Harmonic Structure Suppression

• Published in: IEEE transactions on audio, speech, and language processing speech, and language processing, 2007-01, Vol.15 (1), p.333-345
• Main Authors: Yoshii, K., Goto, M., Okuno, H.G.
• Format: Article
• Language: English
• Subjects: Acoustic signal detection; Adaptation; Adaptive signal detection; Applied sciences; Audio signals; Bass; Content based retrieval; Drum sound recognition; Exact sciences and technology; harmonic structure suppression; Harmonics; Information analysis; Information, signal and communications theory; Instruments; Matching; Miscellaneous; Multiple signal classification; Music information retrieval; Musicians & conductors; Pattern recognition; polyphonic audio signal; Recognition; Rhythm; Signal and communications theory; Signal design; Signal processing; Signal representation. Spectral analysis; Signal, noise; Sound; Spectrogram; spectrogram template; Spectrograms; Telecommunications and information theory; template adaptation; template matching
• ISSN: 1558-7916; 2329-9290; 1558-7924; 2329-9304
• DOI: 10.1109/TASL.2006.876754

This paper describes a system that detects onsets of the bass drum, snare drum, and hi-hat cymbals in polyphonic audio signals of popular songs. Our system is based on a template-matching method that uses power spectrograms of drum sounds as templates. This method calculates the distance between a template and each spectrogram segment extracted from a song spectrogram, using Goto's distance measure originally designed to detect the onsets in drums-only signals. However, there are two main problems. The first problem is that appropriate templates are unknown for each song. The second problem is that it is more difficult to detect drum-sound onsets in sound mixtures including various sounds other than drum sounds. To solve these problems, we propose template-adaptation and harmonic-structure-suppression methods. First of all, an initial template of each drum sound, called a seed template, is prepared. The former method adapts it to actual drum-sound spectrograms appearing in the song spectrogram. To make our system robust to the overlapping of harmonic sounds with drum sounds, the latter method suppresses harmonic components in the song spectrogram before the adaptation and matching. Experimental results with 70 popular songs showed that our template-adaptation and harmonic-structure-suppression methods improved the recognition accuracy and achieved 83%, 58%, and 46% in detecting onsets of the bass drum, snare drum, and hi-hat cymbals, respectively