Signal Processing Methods for Music Transcription

Signal 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.

Riassunto

This text is the first published survey of recent research in signal processing for music transcription, edited and authored by authorities in the field. It covers a range of topics, from the structure and decomposition of signals, to using computational modeling and neural networks for music transcription. The book targets a growing audience interested in MPEG-7 standardization. It serves as an ideal starting point for newcomers and an excellent reference source for people already working in the field. The text is enhanced by a common reference and index.

Dettagli sul prodotto

• Con la collaborazione di: Anssi Klapuri (Editore), Manuel Davy (Editore), Anss Klapuri (Editore), Davy (Editore), Davy (Editore)
• Editore: Springer, Berlin
• Lingue: Inglese
• Contenuto: Libro
• Forma del prodotto: Copertina rigida
• Data pubblicazione: 26.05.2009
• Categoria: Scienze naturali, medicina, informatica, tecnica > Tecnica > Elettronica, elettrotecnica, telecomunicazioni
• EAN: 9780387306674
• ISBN: 978-0-387-30667-4
• Numero di pagine: 440
• Illustrazioni: XII, 440 p. 124 illus.
• Dimensioni (della confezione): 16.6 x 24.2 x 2.9 cm
• Peso (della confezione): 841 g
• Categorie: Maschinenbau, Datenbank, Elektrotechnik, Signal (technisch), Informatik, C, Übersetzung, KI, Data Warehouse, Mustererkennung, Ingenieurswesen, Maschinenbau allgemein, Signalverarbeitung, Natürliche Sprachen und maschinelle Übersetzung, Intelligenz / Künstliche Intelligenz, Künstliche Intelligenz - AI, Datenverarbeitung / Anwendungen / Technik, Ingenieurwissenschaft - Ingenieurwissenschaftler, Elektronik, Nachrichtentechnik, Recherche - Information Retrieval, Informationsmanagement / Data Warehouse, Data Warehousing, Informationsrückgewinnung, Information Retrieval, Database, Audiosignalverarbeitung, Note (musikalisch), Notation, Information Retrieval, engineering, pattern recognition, Signal, Image and Speech Processing, Signal Processing, Automated Pattern Recognition, Speech processing systems, Digital and Analog Signal Processing, Image processing, Information Storage and Retrieval, Natural language & machine translation, Natural Language Processing (NLP), Natural language processing (Computer science)