Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers.
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Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers. 128 pp. Englisch. Nº de ref. del artículo: 9783659745638
Cantidad disponible: 2 disponibles
Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Smita SilkSilk Smita,has Post Graduated from Birla Institute of Technology,Mesra,India in 2015.Her field of interest is Signal Processing,Classical Music, Instrumentation and Control.Sandeep Singh Solanki,Associate professor,Birla In. Nº de ref. del artículo: 158123691
Cantidad disponible: Más de 20 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. Neuware -Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers.Books on Demand GmbH, Überseering 33, 22297 Hamburg 128 pp. Englisch. Nº de ref. del artículo: 9783659745638
Cantidad disponible: 2 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers. Nº de ref. del artículo: 9783659745638
Cantidad disponible: 1 disponibles