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Real-time Speech and Music Classification by Large Audio Feature Space Extraction (Hardcover, 1st ed. 2016) Loot Price: R4,929
Discovery Miles 49 290
Real-time Speech and Music Classification by Large  Audio Feature Space Extraction (Hardcover, 1st ed. 2016): Florian Eyben

Real-time Speech and Music Classification by Large Audio Feature Space Extraction (Hardcover, 1st ed. 2016)

Florian Eyben

Series: Springer Theses

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Loot Price R4,929 Discovery Miles 49 290 | Repayment Terms: R462 pm x 12*

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This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the automated analysis and classification of speech and music. It defines several standard acoustic parameter sets and describes their implementation in a novel, open-source, audio analysis framework called openSMILE, which has been accepted and intensively used worldwide. The book offers extensive descriptions of key methods for the automatic classification of speech and music signals in real-life conditions and reports on the evaluation of the framework developed and the acoustic parameter sets that were selected. It is not only intended as a manual for openSMILE users, but also and primarily as a guide and source of inspiration for students and scientists involved in the design of speech and music analysis methods that can robustly handle real-life conditions.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Springer Theses
Release date: 2016
First published: 2016
Authors: Florian Eyben
Dimensions: 235 x 155 x 21mm (L x W x T)
Format: Hardcover - Cloth over boards
Pages: 298
Edition: 1st ed. 2016
ISBN-13: 978-3-319-27298-6
Categories: Books > Language & Literature > Language & linguistics > Computational linguistics
Books > Professional & Technical > Other technologies > General
Books > Computing & IT > Social & legal aspects of computing > Human-computer interaction
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
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LSN: 3-319-27298-5
Barcode: 9783319272986

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