A Computational Framework for Sound Segregation in Music Signals: An Auditory Scene Analysis Approach for Modeling Perceptual Grouping in Music Listening - Softcover
Synopsis
Music is built from sound, ultimately resulting from an elaborate interaction between the sound-generating properties of physical objects (i.e. music instruments) and the sound perception abilities of the human auditory system. Humans, even without any kind of formal music training, are typically able to extract, almost unconsciously, a great amount of relevant information from a musical signal (e.g. the beat and main melody of a musical piece, or the sound sources playing in a complex musical arrangement). In order to do so, the human auditory system uses a variety of cues for perceptual grouping such as similarity, proximity, harmonicity, common fate, among others. This book proposes a flexible and extensible Computational Auditory Scene Analysis (CASA) framework for modeling perceptual grouping in music listening. Implemented using the open source sound processing framework Marsyas, this work should be specially interesting to researchers in Music Information Retrieval (MIR) and CASA fields, or anyone developing software to perform automatic analysis and processing of sound and music signals.
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About the Author
Luis Gustavo Martins (1974, Portugal) is a full time professor and researcher at the Portuguese Catholic University/CITAR, Porto, Portugal. He holds a PhD in Electrical and Computer Engineering from the University of Porto. His research is mostly on Audio Content Analysis, being actively involved in the Marsyas open source software framework.
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A Computational Framework for Sound Segregation in Music Signals
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Music is built from sound, ultimately resulting from an elaborate interaction between the sound-generating properties of physical objects (i.e. music instruments) and the sound perception abilities of the human auditory system. Humans, even without any kind of formal music training, are typically able to extract, almost unconsciously, a great amount of relevant information from a musical signal (e.g. the beat and main melody of a musical piece, or the sound sources playing in a complex musical arrangement). In order to do so, the human auditory system uses a variety of cues for perceptual grouping such as similarity, proximity, harmonicity, common fate, among others. This book proposes a flexible and extensible Computational Auditory Scene Analysis (CASA) framework for modeling perceptual grouping in music listening. Implemented using the open source sound processing framework Marsyas, this work should be specially interesting to researchers in Music Information Retrieval (MIR) and CASA fields, or anyone developing software to perform automatic analysis and processing of sound and music signals. 248 pp. Englisch. Seller Inventory # 9783838320915
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A Computational Framework for Sound Segregation in Music Signals
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A Computational Framework for Sound Segregation in Music Signals
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A Computational Framework for Sound Segregation in Music Signals | An Auditory Scene Analysis Approach for Modeling Perceptual Grouping in Music Listening
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Taschenbuch. Condition: Neu. A Computational Framework for Sound Segregation in Music Signals | An Auditory Scene Analysis Approach for Modeling Perceptual Grouping in Music Listening | Luís Gustavo Martins | Taschenbuch | 248 S. | Englisch | 2009 | LAP LAMBERT Academic Publishing | EAN 9783838320915 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 101429936
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A Computational Framework for Sound Segregation in Music Signals
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Taschenbuch. Condition: Neu. Neuware -Music is built from sound, ultimately resulting from an elaborate interaction between the sound-generating properties of physical objects (i.e. music instruments) and the sound perception abilities of the human auditory system. Humans, even without any kind of formal music training, are typically able to extract, almost unconsciously, a great amount of relevant information from a musical signal (e.g. the beat and main melody of a musical piece, or the sound sources playing in a complex musical arrangement). In order to do so, the human auditory system uses a variety of cues for perceptual grouping such as similarity, proximity, harmonicity, common fate, among others. This book proposes a flexible and extensible Computational Auditory Scene Analysis (CASA) framework for modeling perceptual grouping in music listening. Implemented using the open source sound processing framework Marsyas, this work should be specially interesting to researchers in Music Information Retrieval (MIR) and CASA fields, or anyone developing software to perform automatic analysis and processing of sound and music signals.Books on Demand GmbH, Überseering 33, 22297 Hamburg 248 pp. Englisch. Seller Inventory # 9783838320915
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A Computational Framework for Sound Segregation in Music Signals : An Auditory Scene Analysis Approach for Modeling Perceptual Grouping in Music Listening
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LAP LAMBERT Academic Publishing, 2009
ISBN 10: 3838320913
ISBN 13: 9783838320915
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Music is built from sound, ultimately resulting from an elaborate interaction between the sound-generating properties of physical objects (i.e. music instruments) and the sound perception abilities of the human auditory system. Humans, even without any kind of formal music training, are typically able to extract, almost unconsciously, a great amount of relevant information from a musical signal (e.g. the beat and main melody of a musical piece, or the sound sources playing in a complex musical arrangement). In order to do so, the human auditory system uses a variety of cues for perceptual grouping such as similarity, proximity, harmonicity, common fate, among others. This book proposes a flexible and extensible Computational Auditory Scene Analysis (CASA) framework for modeling perceptual grouping in music listening. Implemented using the open source sound processing framework Marsyas, this work should be specially interesting to researchers in Music Information Retrieval (MIR) and CASA fields, or anyone developing software to perform automatic analysis and processing of sound and music signals. Seller Inventory # 9783838320915