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008 150903s2006 xxu| o |||| 0|eng d
020 _a9780387328454
_99780387328454
024 7 _a10.1007/0387328459
_2doi
035 _avtls000331001
039 9 _a201509030727
_bVLOAD
_c201404120556
_dVLOAD
_c201404090337
_dVLOAD
_c201401311359
_dstaff
_y201401301159
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTK5102.9
100 1 _aKlapuri, Anssi.
_eeditor.
_9301237
245 1 0 _aSignal Processing Methods for Music Transcription /
_cedited by Anssi Klapuri, Manuel Davy.
264 1 _aBoston, MA :
_bSpringer US,
_c2006.
300 _axii, 440 páginas, 124 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aDavy, Manuel.
_eeditor.
_9301238
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780387306674
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/0-387-32845-9
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c277977
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