ICA-based Single Channel Audio Separation: New Bases and Measures of Distance

• Autorzy: Mika D. , Kleczkowski P.
• Języki publikacji: EN

Abstrakty

EN

Independent Component Analysis (ICA) can be used for single channel audio separation, if a mixed signal is transformed into time-frequency domain and the resulting matrix of magnitude coefficients is processed by ICA. Previous works used only frequency (spectral) vectors and Kullback-Leibler distance measure for this task. New decomposition bases are proposed: time vectors and time-frequency components. The applicability of several different measures of distance of components are analysed. An algorithm for clustering of components is presented. It was tested on mixes of two and three sounds. The perceptual quality of separation obtained with the measures of distance proposed was evaluated by listening tests, indicating “beta” and “correlation” measures as the most appropriate. The “Euclidean” distance is shown to be appropriate for sounds with varying amplitudes. The perceptual effect of the amount of variance used was also evaluated.

Słowa kluczowe

EN

audio unmixing; blind signal separation; independent component analysis; measures of distance

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2011
• Tom: Vol. 36, No. 2
• Strony: 311--331
• Opis fizyczny: Bibliogr. 34 poz., tab., wykr.

Twórcy

autor

Mika D.

autor

Kleczkowski P.

• Studio sQuat Professional Sound Studio Recording Pl. Tysiaclecia PP 1, 22-100 Chełm, Poland,

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