Blind Music Timbre Source Isolation by Multi- resolution Comparison of Spectrum Signatures

Automatic indexing of music instruments for multi-timbre sounds is challenging, especially when partials from different sources are overlapping with each other. Temporal features, which have been successfully applied in monophonic sound timbre identification, failed to isolate music instrument in multi-timbre objects, since the detection of the start and end position of each music segment unit is very difficult. Spectral features of MPEG7 and other popular features provide economic computation but contain limited information about timbre. Being compared to the spectral features, spectrum signature features have less information loss; therefore may identify sound sources in multitimbre music objects with higher accuracy. However, the high dimensionality of spectrum signature feature set requires intensive computing and causes estimation efficiency problem. To overcome these problems, the authors developed a new multi-resolution system with an iterative spectrum band matching device to provide fast and accurate recognition.