Multi-Pitch Estimation (Record no. 85188)

000 -LEADER
fixed length control field 03555nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-031-02558-7
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730164002.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2009 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031025587
-- 978-3-031-02558-7
082 04 - CLASSIFICATION NUMBER
Call Number 621.3
100 1# - AUTHOR NAME
Author Christensen, Mads.
245 10 - TITLE STATEMENT
Title Multi-Pitch Estimation
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2009.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVII, 141 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Speech and Audio Processing,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Fundamentals -- Statistical Methods -- Filtering Methods -- Subspace Methods -- Amplitude Estimation.
520 ## - SUMMARY, ETC.
Summary, etc Periodic signals can be decomposed into sets of sinusoids having frequencies that are integer multiples of a fundamental frequency. The problem of finding such fundamental frequencies from noisy observations is important in many speech and audio applications, where it is commonly referred to as pitch estimation. These applications include analysis, compression, separation, enhancement, automatic transcription and many more. In this book, an introduction to pitch estimation is given and a number of statistical methods for pitch estimation are presented. The basic signal models and associated estimation theoretical bounds are introduced, and the properties of speech and audio signals are discussed and illustrated. The presented methods include both single- and multi-pitch estimators based on statistical approaches, like maximum likelihood and maximum a posteriori methods, filtering methods based on both static and optimal adaptive designs, and subspace methods based on the principles of subspace orthogonality and shift-invariance. The application of these methods to analysis of speech and audio signals is demonstrated using both real and synthetic signals, and their performance is assessed under various conditions and their properties discussed. Finally, the estimators are compared in terms of computational and statistical efficiency, generalizability and robustness. Table of Contents: Fundamentals / Statistical Methods / Filtering Methods / Subspace Methods / Amplitude Estimation.
700 1# - AUTHOR 2
Author 2 Jakobsson, Andreas.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-02558-7
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2009.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Acoustical engineering.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical and Electronic Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering Acoustics.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1932-1678
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-- ZDB-2-SXSC

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