Discovering Musical Structure in Audio Recordings
ICMAI '02 Proceedings of the Second International Conference on Music and Artificial Intelligence
Music scene-adaptive harmonic dictionary for unsupervised note-event detection
IEEE Transactions on Audio, Speech, and Language Processing
Flexible harmonic temporal structure for modeling musical instrument
ICEC'10 Proceedings of the 9th international conference on Entertainment computing
A music retrieval system based on query-by-singing for karaoke jukebox
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
Harmonic source separation using prestored spectra
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
An auditory model based approach for melody detection in polyphonic musical recordings
CMMR'04 Proceedings of the Second international conference on Computer Music Modeling and Retrieval
Adaptive music retrieval---a state of the art
Multimedia Tools and Applications
Hi-index | 0.00 |
This paper describes a predominant-F/sub 0/ (fundamental frequency) estimation method called PreFEst, which can detect melody and bass lines in monaural audio signals containing sounds of various instruments, While most previous methods premised mixtures of a few sounds and had difficulty dealing with such complex signals, our method can estimate the F/sub 0/ of the melody and bass lines without assuming the number of sound sources in compact-disc recordings. In this paper we propose the following three extensions to our previous PreFEst to make it more adaptive and flexible: introducing multiple harmonic-structure tone models, estimating the shape of tone models, and introducing a prior distribution of its shape and F/sub 0/ estimates These extensions were implemented by the MAP (maximum a posteriori probability) estimation by using the expectation-maximization algorithm. Experimental results with compact-disc recordings showed that our real-time system based on the extended PreFEst achieved performance improvement.