Drum Transcription From Multichannel Recordings With Non-Negative Matrix Factorization

Automatic drum transcription enables handling symbolic data instead of plain acoustic information in music information retrieval applications. Usually the input to the transcription system is single-channel audio, and as a result the proposed solutions are designed for this kind of input. However, in studio environment the multichannel recording of the drums is often available. This paper proposes an extension to a non-negative matrix factorization drum transcription method to handle multichannel data. The method creates spectral templates for all target drums from all available channels, and in transcription estimates time-varying gains for each of them so that the sum approximates the recorded signal. Sound event onsets are detected from the estimated gains. The system is evaluated with multichannel data from a publicly available data set, and compared with other methods. The results suggest that the use of multiple channels instead of a single-channel mix improves the transcription result.