Separation of Music Signals by Harmonic Structure Modeling
Zhang, Yun-gang, Zhang, Chang-shui
–Neural Information Processing Systems
Separation of music signals is an interesting but difficult problem. It is helpful for many other music researches such as audio content analysis. In this paper, a new music signal separation method is proposed, which is based on harmonic structure modeling. The main idea of harmonic structure modelingis that the harmonic structure of a music signal is stable, so a music signal can be represented by a harmonic structure model. Accordingly, acorresponding separation algorithm is proposed. The main idea is to learn a harmonic structure model for each music signal in the mixture, and then separate signals by using these models to distinguish harmonic structures of different signals. Experimental results show that the algorithm can separate signals and obtain not only a very high Signalto-Noise Ratio(SNR) but also a rather good subjective audio quality.
Neural Information Processing Systems
Dec-31-2006
- Industry:
- Leisure & Entertainment (0.87)
- Media > Music (0.87)
- Technology:
- Information Technology
- Artificial Intelligence > Speech (0.31)
- Data Science > Data Mining (0.35)
- Information Technology