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001 978-0-387-32845-4
003 DE-He213
005 20170628033305.0
007 cr nn 008mamaa
008 100301s2006 xxu| s |||| 0|eng d
020 _a9780387328454
_9978-0-387-32845-4
024 7 _a10.1007/0-387-32845-9
_2doi
050 4 _aTK5102.9
050 4 _aTA1637-1638
050 4 _aTK7882.S65
072 7 _aTTBM
_2bicssc
072 7 _aUYS
_2bicssc
072 7 _aTEC008000
_2bisacsh
072 7 _aCOM073000
_2bisacsh
082 0 4 _a621.382
_223
100 1 _aKlapuri, Anssi.
_eeditor.
245 1 0 _aSignal Processing Methods for Music Transcription
_h[electronic resource] /
_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 _aonline resource
_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
912 _aZDB-2-ENG
999 _c14509
_d14509