Music-content-adaptive robust principal component analysis for a semantically consistent separation of foreground and background in music audio signals | Zendy

Hélène Papadopoulos | Zendy; Daniel P. W. Ellis | Zendy

Open Access

Music-content-adaptive robust principal component analysis for a semantically consistent separation of foreground and background in music audio signals

Author(s) -

Hélène Papadopoulos,

Daniel P. W. Ellis

Publication year - 2014

Publication title -

hal (le centre pour la communication scientifique directe)

Language(s) - English

Resource type - Conference proceedings

Subject(s) - robust principal component analysis , principal component analysis , computer science , source separation , set (abstract data type) , rank (graph theory) , content (measure theory) , audio signal processing , speech recognition , artificial intelligence , component (thermodynamics) , pattern recognition (psychology) , process (computing) , field (mathematics) , audio signal , mathematics , speech coding , mathematical analysis , physics , thermodynamics , combinatorics , pure mathematics , programming language , operating system

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