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An Introduction to Audio Content Analysis Applications in Signal Processing and Music Informatics,9781118266823
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An Introduction to Audio Content Analysis Applications in Signal Processing and Music Informatics



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Wiley-IEEE Press
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With the proliferation of digital audio distribution over digital media, audio content analysis is fast becoming a requirement for designers of intelligent signal-adaptive audio processing systems. Written by a well-known expert in the field, this book provides quick access to different analysis algorithms and allows comparison between different approaches to the same task, making it useful for newcomers to audio signal processing and industry experts alike. A review of relevant fundamentals in audio signal processing, psychoacoustics, and music theory, as well as downloadable MATLAB files are also included.

Author Biography

Alexander Lerch, PhD, is Managing Director and co-owner of zplane development, a research and development firm of licensable technology for digital audio signal processing for both the music software industry and major audio content distributors. Dr. Lerch also teaches audio content analysis at the Technical University of Berlin.

Table of Contents

Prefacep. xiii
Acronymsp. xv
List of Symbolsp. xix
Introductionp. 1
Audio Contentp. 3
A Generalized Audio Content Analysis Systemp. 4
Fundamentalsp. 7
Audio Signalsp. 7
Periodic Signalsp. 7
Random Signalsp. 9
Sampling and Quantizationp. 9
Statistical Signal Descriptionp. 13
Signal Processingp. 14
Convolutionp. 14
Block-Based Processingp. 18
Fourier Transformp. 20
Constant Q Transformp. 23
Auditory Filterbanksp. 24
Correlation Functionp. 24
Linear Predictionp. 28
Instantaneous Featuresp. 31
Audio Pre-Processingp. 33
Down-Mixingp. 33
DC Removalp. 33
Normalizationp. 34
Down-Samplingp. 34
Other Pre-Processing Optionsp. 35
Statistical Propertiesp. 35
Arithmetic Meanp. 36
Geometric Meanp. 36
Harmonic Meanp. 36
Generalized Meanp. 26
Centroidp. 37
Variance and Standard Deviationp. 37
Skewnessp. 38
Kurtosisp. 39
Generalized Central Momentsp. 40
Quantiles and Quantile Rangesp. 40
Spectral Shapep. 41
Spectral Rolloffp. 42
Spectral Fluxp. 44
Spectral Centroidp. 45
Spectral Spreadp. 47
Spectral Decreasep. 48
Spectral Slopep. 49
Mel Frequency Cepstral Coefficientsp. 51
Signal Propertiesp. 54
Tonalnessp. 54
Autocorrelation Coefficientsp. 61
Zero Crossing Ratep. 62
Feature Post-Processingp. 53
Derived Featuresp. 64
Normalization and Mappingp. 65
Subfeaturesp. 66
Feature Dimensionality Reductionp. 66
Intensityp. 71
Human Perception of Intensity and Loudnessp. 71
Representation of Dynamics in Musicp. 73
Featuresp. 73
Root Mean Squarep. 73
Peak Envelopep. 76
Psycho-Acoustic Loudness Featuresp. 77
EBU R128p. 78
Tonal Analysisp. 79
Human Perception of Pitchp. 79
Pitch Scalesp. 79
Chroma Perceptionp. 81
Representation of Pitch in Musicp. 82
Pitch Classes and Namesp. 82
Intervalsp. 83
Root Note, Mode, and Keyp. 83
Chords and Harmonyp. 86
The Frequency of Musical Pitchp. 88
Fundamental Frequency Detectionp. 91
Detection Accuracyp. 92
Pre-Processingp. 94
Monophonic Input Signalsp. 97
Polyphonic Input Signalsp. 103
Tuning Frequency Estimationp. 106
Key Detectionp. 108
Pitch Chromap. 108
Key Recognitionp. 112
Chord Recognitionp. 116
Temporal Analysisp. 119
Human Perception of Temporal Eventsp. 119
Onsetsp. 119
Tempo and Meterp. 122
Rhythmp. 122
Timingp. 123
Representation of Temporal Events in Musicp. 123
Tempo and Time Signaturep. 123
Note Valuep. 124
Onset Detectionp. 124
Novelty Functionp. 125
Peak Pickingp. 127
Evaluationp. 128
Beat Histogramp. 133
Beat Histogram Featuresp. 134
Detection of Tempo and Beat Phasep. 135
Detection of Meter and Downbeatp. 136
Alignmentp. 139
Dynamic Time Warpingp. 139
Examplep. 143
Common Variantsp. 144
Optimizationsp. 145
Audio-to-Audio Alignmentp. 146
Ground Truth Data for Evaluationp. 147
Audio-to-Score Alignmentp. 148
Real-Time Systemsp. 148
Non-Real-Time Systemsp. 149
Musical Genre, Similarity, and Moodp. 151
Musical Genre Classificationp. 151
Musical Genrep. 152
Feature Extractionp. 154
Classificationp. 155
Related Research Fieldsp. 156
Music Similarity Detectionp. 156
Mood Classificationp. 158
Instrument Recognitionp. 161
Audio Fingerprintingp. 163
Fingerprint Extractionp. 164
Fingerprint Matchingp. 165
Fingerprinting System: Examplep. 166
Music Performance Analysisp. 169
Musical Communicationp. 169
Scorep. 169
Music Performancep. 170
Productionp. 172
Recipientp. 172
Music Performance Analysisp. 172
Analysis Datap. 173
Research Resultsp. 177
Convolution Propertiesp. 181
Identityp. 181
Commutativityp. 181
Associativityp. 182
Distributivityp. 183
Circularityp. 183
Fourier Transformp. 185
Properties of the Fourier Transformationp. 186
Inverse Fourier Transformp. 186
Superpositionp. 186
Convolution and Multiplicationp. 186
Parseval's Theoremp. 187
Time and Frequency Shiftp. 188
Symmetryp. 188
Time and Frequency Scalingp. 189
Derivativesp. 190
Spectrum of Example Time Domain Signalsp. 190
Delta Functionp. 190
Constantp. 191
Cosinep. 191
Rectangular Windowp. 191
Delta Pulsep. 191
Transformation of Sampled Time Signalsp. 192
Short Time Fourier Transform of Continuous Signalsp. 192
Window Functionsp. 193
Discrete Fourier Transformp. 195
Window Functionsp. 196
Fast Fourier Transformp. 197
Principal Component Analysisp. 199
Computation of the Transformation Matrixp. 200
Interpretation of the Transformation Matrixp. 200
Software for Audio Analysisp. 201
Software Frameworks and Applicationsp. 202
Marsyasp. 202
CLAMp. 202
jMIRp. 203
CoMTRVAp. 203
Sonic Visualiserp. 203
Software Libraries and Toolboxesp. 204
Feature Extractionp. 204
Plugin Interfacesp. 205
Other Softwarep. 206
Referencesp. 207
Indexp. 243
Table of Contents provided by Ingram. All Rights Reserved.

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