Lerch - Lerch: Introduction to Audio Conte

Lerch: Introduction to Audio Conte

Medium: Buch

ISBN: 978-1-118-26682-3

Verlag: Wiley John + Sons

Erscheinungstermin: 09.10.2012

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List of Figures xiiiList of Tables xviiPreface xixAcronyms xxiList of Symbols xxv1 Introduction 11.1 Audio Content 31.2 A Generalized Audio Content Analysis System 42 Fundamentals 72.1 Audio Signals 72.1.1 Periodic Signals 72.1.2 Random Signals 92.1.3 Sampling and Quantization 92.1.4 Statistical Signal Description 132.2 Signal Processing 142.2.1 Convolution 142.2.2 BlockBased Processing 182.2.3 Fourier Transform 202.2.4 Constant Q Transform 232.2.5 Auditory Filterbanks 242.2.6 Correlation Function 242.2.7 Linear Prediction 283 Instantaneous Features 313.1 Audio PreProcessing 333.1.1 DownMixing 333.1.2 DC Removal 333.1.3 Normalization 343.1.4 DownSampling 343.1.5 Other PreProcessing Options 353.2 Statistical Properties 353.2.1 Arithmetic Mean 363.2.2 Geometric Mean 363.2.3 Harmonic Mean 363.2.4 Generalized Mean 363.2.5 Centroid 373.2.6 Variance and Standard Deviation 373.2.7 Skewness 383.2.8 Kurtosis 393.2.9 Generalized Central Moments 403.2.10 Quantiles and Quantile Ranges 403.3 Spectral Shape 413.3.1 Spectral Rolloff 423.3.2 Spectral Flux 443.3.3 Spectral Centroid 453.3.4 Spectral Spread 473.3.5 Spectral Decrease 483.3.6 Spectral Slope 493.3.7 Mel Frequency Cepstral Coefficients 513.4 Signal Properties 543.4.1 Tonalness 543.4.2 Auto Correlation Coefficients 613.4.3 Zero Crossing Rate 623.5 Feature PostProcessing 633.5.1 Derived Features 643.5.2 Normalization and Mapping 653.5.3 Subfeatures 663.5.4 Feature Dimensionality Reduction 664 Intensity 714.1 Human Perception of Intensity and Loudness 714.2 Representation of Dynamics in Music 734.3 Features 734.3.1 Root Mean Square 734.4 Peak Envelope 764.5 PsychoAcoustic Loudness Features 774.5.1 EBU R128 785 Tonal Analysis 795.1 Human Perception of Pitch 795.1.1 Pitch Scales 795.1.2 Chroma Perception 815.2 Representation of Pitch in Music 825.2.1 Pitch Classes and Names 825.2.2 Intervals 835.2.3 Root Note, Mode, and Key 835.2.4 Chords and Harmony 865.2.5 The Frequency of Musical Pitch 885.3 Fundamental Frequency Detection 915.3.1 Detection Accuracy 925.3.2 PreProcessing 945.3.3 Monophonic Input Signals 975.3.4 Polyphonic Input Signals 1035.4 Tuning Frequency Estimation 1065.5 Key Detection 1085.5.1 Pitch Chroma 1085.5.2 Key Recognition 1125.6 Chord Recognition 1166 Temporal Analysis 1196.1 Human Perception of Temporal Events 1196.1.1 Onsets 1196.1.2 Tempo and Meter 1226.1.3 Rhythm 1226.1.4 Timing 1236.2 Representation of Temporal Events in Music 1236.2.1 Tempo and Time Signature 1236.2.2 Note Value 1246.3 Onset Detection 1246.3.1 Novelty Function 1256.4 Beat Histogram 1336.4.1 Beat Histogram Features 1346.5 Detection of Tempo and Beat Phase 1356.6 Detection of Meter and Downbeat 1367 Alignment 1397.1 Dynamic Time Warping 1397.1.1 Example 1437.1.2 Common Variants 1447.1.3 Optimizations 1457.2 AudiotoAudioAlignment 1467.2.1 Ground Truth Data for Evaluation 1477.3 AudiotoScore Alignment 1487.3.1 RealTime Systems 1487.3.2 Non RealTime Systems 1498 Musical Genre, Similarity and Mood 1518.1 Musical Genre Classification 1518.1.1 Musical Genre 1528.1.2 Feature Extraction 1548.1.3 Classification 1558.2 Related Research Fields 1568.2.1 Music Similarity Detection 1568.2.2 Mood Classification 1588.2.3 Instrument Recognition 1619 Audio Fingerprinting 1639.1 Fingerprint Extraction 1649.2 Fingerprint Matching 1659.3 Fingerprinting System: Example 16610 Music Performance Analysis 16910.1 Musical Communication 16910.1.1 Score 16910.1.2 Music Performance 17010.1.3 Production 17210.1.4 Recipient 17210.2 Music Performance Analysis 17210.2.1 Analysis Data 17410.2.2 Research Results 177A Convolution Properties 181A.1 Identity 181A.2 Commutativity 181A.3 Associativity 182A.4 Distributivity 183A.5 Circularity 183B Fourier Transform 185B.1 Properties of the Fourier Transformation 186B.1.1 Inverse Fourier Transform 186B.1.2 Superposition 186B.1.3 Convolution and Multiplication 186B.1.4 Parseval's Theorem 187B.1.5 Time and Frequency Shift 188B.1.6 Symmetry 188B.1.7 Time and Frequency Scaling 189B.1.8 Derivatives 190B.2 Spectrum of Example Time Domain Signals 190B.2.1 Delta Function 190B.2.2 Constant 190B.2.3 Cosine 190B.2.4 Rectangular Window 191B.2.5 Delta Pulse 191B.3 Transformation of sampled time signals 191B.4 Short Time Fourier Transform of Continuous Signals 192B.4.1 Window Functions 193B.5 Discrete Fourier Transform 195B.5.1 Window Functions 196B.5.2 Fast Fourier Transform 197C Principal Component Analysis 199C.1 Computation of the Transformation Matrix 200C.2 Interpretation of the Transformation Matrix 200D Software for Audio Analysis 201D.1 Software Frameworks & Applications 202D.1.1 Marsyas 202D.1.2 CLAM 202D.1.3 jMIR 203D.1.4 CoMIRVA 203D.1.5 Sonic Visualiser 203D.2 Software Libraries & Toolboxes 204D.2.1 Feature Extraction 204D.2.2 Plugin Interfaces 205D.2.3 Other Software 206References 207Index 237