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Audio Source Separation Using Independent Component Analysis and Beam Formation

Description: Audio Source Separation Using Independent Component Analysis and Beam Formation by Kishan Panaganti Project Report from the year 2013 in the subject Audio Engineering, grade: 10, , course: ECE, language: English, abstract: Audio source separation is the problem of automated separation of audio sources present in a room, using a set of differently placed microphones, capturing the auditory scene. The whole problem resembles the task a human can solve in a cocktail party situation, where using two sensors (ears), the brain can focus on a specific source of interest, suppressing all other sources present (cocktail party problem). For computational and conceptual simplicity this problem is often represented as a linear transformation of the original audio signals. In other words, each component (multivariate signal) of the representation is a linear combination of the original variables (original subcomponents). In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents by assuming that the subcomponents are non-Gaussian signals and that they are all statistically independent from each other. Such a representation seems to capture the essential structure of the data in many applications. Here we separate audio using different criteria suggested for ICA, being PCA (Principal Component Analysis), Non-gaussianity maximization using kurtosis and neg-entropy methods, frequency domain approach using non-gaussianity maximization and beamforming. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description Project Report from the year 2013 in the subject Audio Engineering, grade: 10, course: ECE, language: English, abstract: Audio source separation is the problem of automated separation of audio sources present in a room, using a set of differently placed microphones, capturing the auditory scene. The whole problem resembles the task a human can solve in a cocktail party situation, where using two sensors (ears), the brain can focus on a specific source of interest, suppressing all other sources present (cocktail party problem). For computational and conceptual simplicity this problem is often represented as a linear transformation of the original audio signals. In other words, each component (multivariate signal) of the representation is a linear combination of the original variables (original subcomponents). In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents by assuming that the subcomponents are non-Gaussian signals and that they are all statistically independent from each other. Such a representation seems to capture the essential structure of the data in many applications. Here we separate audio using different criteria suggested for ICA, being PCA (Principal Component Analysis), Non-gaussianity maximization using kurtosis and neg-entropy methods, frequency domain approach using non-gaussianity maximization and beamforming. Details ISBN3656588864 Author Kishan Panaganti Pages 32 Language English Year 2014 ISBN-10 3656588864 ISBN-13 9783656588863 Format Paperback Publication Date 2014-02-18 Short Title AUDIO SOURCE SEPARATION USING Media Book Country of Publication United States Illustrations Illustrations, black and white Publisher Grin Publishing Imprint Grin Verlag Audience General/Trade We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:100347280;

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Audio Source Separation Using Independent Component Analysis and Beam Formation

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ISBN-13: 9783656588863

Book Title: Audio Source Separation Using Independent Component Analysis and

Publisher: GRIN Verlag

Item Height: 210 mm

Subject: Engineering & Technology, Mechanics

Publication Year: 2014

Number of Pages: 32 Pages

Publication Name: Audio Source Separation Using Independent Component Analysis and Beam Formation

Language: English

Type: Textbook

Item Weight: 54 g

Author: Kishan Panaganti

Item Width: 148 mm

Format: Paperback

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