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Author Giannoulis, Dimitrios ♦ Klapuri, Anssi ♦ Plumbley, Mark D.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Mixture Signal ♦ Spectral Region ♦ Feature Vector Element ♦ Musical Instrument Sound ♦ Feature Technique ♦ Local Spectral Feature ♦ Reliable Information ♦ Extensive Availability ♦ Environmental Sound ♦ Animal Sound ♦ Harmonic Sound ♦ Mask Estimation Algorithm ♦ Sound Source ♦ Baseline Method
Abstract A method based on local spectral features and missing feature techniques is proposed for the recognition of harmonic sounds in mixture signals. A mask estimation algorithm is proposed for identifying spectral regions that contain reliable information for each sound source and then bounded marginalization is employed to treat the feature vector elements that are determined as unreliable. The proposed method is tested on musical instrument sounds due to the extensive availability of data but it can be applied on other sounds (i.e. animal sounds, environmental sounds), whenever these are harmonic. In simulations the proposed method clearly outperformed a baseline method for mixture signals. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study