000			03649nam a22004575i 4500
001			978-0-387-32845-4
003			DE-He213
005			20250710083950.0
007			cr nn 008mamaa
008			100301s2006 xxu| s |||| 0|eng d
020			_a9780387328454 _a99780387328454
024	7		_a10.1007/0-387-32845-9 _2doi
082	0	4	_a621.382 _223
100	1		_aKlapuri, Anssi. _eeditor.
245	1	0	_aSignal Processing Methods for Music Transcription _h[recurso electrónico] / _cedited by Anssi Klapuri, Manuel Davy.
264		1	_aBoston, MA : _bSpringer US, _c2006.
300			_aXII, 440p. 124 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aFoundations -- to Music Transcription -- An Introduction to Statistical Signal Processing and Spectrum Estimation -- Sparse Adaptive Representations for Musical Signals -- Rhythm and Timbre Analysis -- Beat Tracking and Musical Metre Analysis -- Unpitched Percussion Transcription -- Automatic Classification of Pitched Musical Instrument Sounds -- Multiple Fundamental Frequency Analysis -- Multiple Fundamental Frequency Estimation Based on Generative Models -- Auditory Model-Based Methods for Multiple Fundamental Frequency Estimation -- Unsupervised Learning Methods for Source Separation in Monaural Music Signals -- Entire Systems, Acoustic and Musicological Modelling -- Auditory Scene Analysis in Music Signals -- Music Scene Description -- Singing Transcription.
520			_aSignal Processing Methods for Music Transcription is the first book dedicated to uniting research related to signal processing algorithms and models for various aspects of music transcription such as pitch analysis, rhythm analysis, percussion transcription, source separation, instrument recognition, and music structure analysis. Following a clearly structured pattern, each chapter provides a comprehensive review of the existing methods for a certain subtopic while covering the most important state-of-the-art methods in detail. The concrete algorithms and formulas are clearly defined and can be easily implemented and tested. A number of approaches are covered, including, for example, statistical methods, perceptually-motivated methods, and unsupervised learning methods. The text is enhanced by a common reference and index. This book aims to serve as an ideal starting point for newcomers and an excellent reference source for people already working in the field. Researchers and graduate students in signal processing, computer science, acoustics and music will primarily benefit from this text. It could be used as a textbook for advanced courses in music signal processing. Since it only requires a basic knowledge of signal processing, it is accessible to undergraduate students.
650		0	_aENGINEERING.
650		0	_aINFORMATION STORAGE AND RETRIEVAL SYSTEMS.
650		0	_aTRANSLATORS (COMPUTER PROGRAMS).
650		0	_aOPTICAL PATTERN RECOGNITION.
650	1	4	_aENGINEERING.
650	2	4	_aSIGNAL, IMAGE AND SPEECH PROCESSING.
650	2	4	_aPATTERN RECOGNITION.
650	2	4	_aINFORMATION STORAGE AND RETRIEVAL.
650	2	4	_aLANGUAGE TRANSLATION AND LINGUISTICS.
700	1		_aDavy, Manuel. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387306674
856	4	0	_uhttp://dx.doi.org/10.1007/0-387-32845-9 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-ENG
942			_2ddc _cER
999			_c57210 _d57210