Part 1 Foundations: Introduction to Music Transcription.- An Introduction to Statistical Signal Processing and Spectrum Estimation.- Sparse Adaptive Representations for Musical Signals.- Part II Rhythm and Timbre Analysis: Beat Tracking and Musical Metre Analysis.- Unpitched Percussion Transcription.- Automatic Classification of Pitched Musical Instrument Sounds.- Part III Multiple Fundamental Frequency Analysis: Multiple F0 Frequency Estimation Based on Generative Models.- Auditory-Model Based Methods for Multiple Fundamental Frequency Estimation.- Unsupervised Learning Methods for Source Separation.- Part IV Entire Systems, Acoustic and Musicological Modeling: Auditory Scene Analysis in Music Signals.- Music Scene Description.- Singing Transcription.- References.- Index.
This book serves 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.
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.