Signal Processing Methods for Music Transcription

Cover -- Contents -- Preface -- List of Contributors -- Part I: Foundations -- CH 1 Introduction to Music Transcription -- 1.1 Terminology and Concepts -- 1.2 Perspectives on Music Transcription -- 1.3 Outline -- CH 2 An Introduction to Statistical Signal Processing and Spectrum Estimation -- 2.1 Frequency, Time-Frequency, and Cepstral Representations -- 2.2 Basic Statistical Methods -- 2.3 Bayesian Statistical Methods -- 2.4 Pattern Recognition Methods -- CH 3 Sparse Adaptive Representations for Musical Signals -- 3.1 Introduction -- 3.2 Parametric Representations -- 3.3 Waveform Representations -- 3.4 Conclusion -- Part II: Rhythm and Timbre Analysis -- CH 4 Beat Tracking and Musical Metre Analysis -- 4.1 Introduction -- 4.2 Summary of Beat-Tracking Approaches -- 4.3 Musical Background to Rhythmic Structure -- 4.4 Onset Detection -- 4.5 Rule-Based Approaches -- 4.6 Autocorrelation Methods -- 4.7 Oscillating Filter Approaches -- 4.8 Histogramming Methods -- 4.9 Multiple Agent Approaches -- 4.10 Probabilistic Models -- 4.11 Comparison of Algorithms -- 4.12 Conclusions -- CH 5 Unpitched Percussion Transcription -- 5.1 Introduction -- 5.2 Pattern Recognition Approaches -- 5.3 Separation-Based Approaches -- 5.4 Musicological Modelling -- 5.5 Conclusions -- 5.6 Acknowledgements -- CH 6 Automatic Classification of Pitched Musical Instrument Sounds -- 6.1 Introduction -- 6.2 Methodology -- 6.3 Features and Their Selection -- 6.4 Classification Techniques -- 6.5 Classification of Isolated Sounds -- 6.6 Classification of Sounds from Music Files -- 6.7 Conclusions -- Part III: Multiple Fundamental Frequency Analysis -- CH 7 Multiple Fundamental Frequency Estimation Based on Generative Models -- 7.1 Noisy Sum-of-Sines Models -- 7.2 Off-line Approaches -- 7.3 On-Line Approaches -- 7.4 Other On-Line Bayesian Approaches -- 7.5 Conclusions -- CH 8 Auditory Model-Based Methods for Multiple Fundamental Frequency Estimation -- 8.1 Introduction -- 8.2 Musical Sounds and F0 Estimation -- 8.3 Pitch Perception Models -- 8.4 Using an Auditory Model as a Front End -- 8.5 Computational Multiple FO Estimation Methods -- 8.6 Conclusions -- CH 9 Unsupervised Learning Methods for Source Separation in Monaural Music Signals -- 9.1 Introduction -- 9.2 Signal Model -- 9.3 Independent Component Analysis -- 9.4 Sparse Coding -- 9.5 Non-Negative Matrix Factorization -- 9.6 Prior Information about Sources -- 9.7 Further Processing of the Components -- 9.8 Time-Varying Components -- 9.9 Evaluation of the Separation Quality -- 9.10 Summary and Discussion -- Part IV: Entire Systems, Acoustic and Musicological Modelling -- CH 10 Auditory Scene Analysis in Music Signals -- 10.1 Introduction -- 10.2 Strategy for Music Scene Analysis -- 10.3 Probabilistic Models for Music Scene Analysis -- 10.4 Conclusion: From Grouping to Generative Estimation -- CH 11 Music Scene Description -- 11.1 Introduction -- 11.2 Estimating Melody and Bass Lines -- 11.3 Estimating Beat Structure -- 11.4 Estimating Drums.