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008 120409s2012 njua ob 001 0 eng
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019 _a817746964
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020 _a9781118393550
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035 _a(OCoLC)816310153
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050 4 _aTK7881.4
_b.L485 2012
072 7 _aCOM
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082 0 4 _a006.4/5
_223
049 _aMAIN
100 1 _aLerch, Alexander.
245 1 3 _aAn introduction to audio content analysis :
_bapplications in signal processing and music informatics /
_cAlexander Lerch.
260 _aHoboken, N.J. :
_bWiley,
_c©2012.
300 _a1 online resource (xxii, 248 pages)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 _aMachine generated contents note: 1.1. Audio Content -- 1.2.A Generalized Audio Content Analysis System -- 2.1. Audio Signals -- 2.1.1. Periodic Signals -- 2.1.2. Random Signals -- 2.1.3. Sampling and Quantization -- 2.1.4. Statistical Signal Description -- 2.2. Signal Processing -- 2.2.1. Convolution -- 2.2.2. Block-Based Processing -- 2.2.3. Fourier Transform -- 2.2.4. Constant Q Transform -- 2.2.5. Auditory Filterbanks -- 2.2.6. Correlation Function -- 2.2.7. Linear Prediction -- 3.1. Audio Pre-Processing -- 3.1.1. Down-Mixing -- 3.1.2. DC Removal -- 3.1.3. Normalization -- 3.1.4. Down-Sampling -- 3.1.5. Other Pre-Processing Options -- 3.2. Statistical Properties -- 3.2.1. Arithmetic Mean -- 3.2.2. Geometric Mean -- 3.2.3. Harmonic Mean -- 3.2.4. Generalized Mean -- 3.2.5. Centroid -- 3.2.6. Variance and Standard Deviation -- 3.2.7. Skewness -- 3.2.8. Kurtosis -- 3.2.9. Generalized Central Moments -- 3.2.10. Quantiles and Quantile Ranges -- 3.3. Spectral Shape -- 3.3.1. Spectral Rolloff.
505 0 _aContents note continued: 3.3.2. Spectral Flux -- 3.3.3. Spectral Centroid -- 3.3.4. Spectral Spread -- 3.3.5. Spectral Decrease -- 3.3.6. Spectral Slope -- 3.3.7. Mel Frequency Cepstral Coefficients -- 3.4. Signal Properties -- 3.4.1. Tonalness -- 3.4.2. Autocorrelation Coefficients -- 3.4.3. Zero Crossing Rate -- 3.5. Feature Post-Processing -- 3.5.1. Derived Features -- 3.5.2. Normalization and Mapping -- 3.5.3. Subfeatures -- 3.5.4. Feature Dimensionality Reduction -- 4.1. Human Perception of Intensity and Loudness -- 4.2. Representation of Dynamics in Music -- 4.3. Features -- 4.3.1. Root Mean Square -- 4.4. Peak Envelope -- 4.5. Psycho-Acoustic Loudness Features -- 4.5.1. EBU R128 -- 5.1. Human Perception of Pitch -- 5.1.1. Pitch Scales -- 5.1.2. Chroma Perception -- 5.2. Representation of Pitch in Music -- 5.2.1. Pitch Classes and Names -- 5.2.2. Intervals -- 5.2.3. Root Note, Mode, and Key -- 5.2.4. Chords and Harmony -- 5.2.5. The Frequency of Musical Pitch -- 5.3. Fundamental Frequency Detection.
505 0 _aContents note continued: 5.3.1. Detection Accuracy -- 5.3.2. Pre-Processing -- 5.3.3. Monophonic Input Signals -- 5.3.4. Polyphonic Input Signals -- 5.4. Tuning Frequency Estimation -- 5.5. Key Detection -- 5.5.1. Pitch Chroma -- 5.5.2. Key Recognition -- 5.6. Chord Recognition -- 6.1. Human Perception of Temporal Events -- 6.1.1. Onsets -- 6.1.2. Tempo and Meter -- 6.1.3. Rhythm -- 6.1.4. Timing -- 6.2. Representation of Temporal Events in Music -- 6.2.1. Tempo and Time Signature -- 6.2.2. Note Value -- 6.3. Onset Detection -- 6.3.1. Novelty Function -- 6.3.2. Peak Picking -- 6.3.3. Evaluation -- 6.4. Beat Histogram -- 6.4.1. Beat Histogram Features -- 6.5. Detection of Tempo and Beat Phase -- 6.6. Detection of Meter and Downbeat -- 7.1. Dynamic Time Warping -- 7.1.1. Example -- 7.1.2.Common Variants -- 7.1.3. Optimizations -- 7.2. Audio-to-Audio Alignment -- 7.2.1. Ground Truth Data for Evaluation -- 7.3. Audio-to-Score Alignment -- 7.3.1. Real-Time Systems M -- 7.3.2. Non-Real-Time Systems.
505 0 _aContents note continued: 8.1. Musical Genre Classification -- 8.1.1. Musical Genre -- 8.1.2. Feature Extraction -- 8.1.3. Classification -- 8.2. Related Research Fields -- 8.2.1. Music Similarity Detection -- 8.2.2. Mood Classification -- 8.2.3. Instrument Recognition -- 9.1. Fingerprint Extraction -- 9.2. Fingerprint Matching -- 9.3. Fingerprinting System: Example -- 10.1. Musical Communication -- 10.1.1. Score -- 10.1.2. Music Performance -- 10.1.3. Production -- 10.1.4. Recipient -- 10.2. Music Performance Analysis -- 10.2.1. Analysis Data -- 10.2.2. Research Results -- A.1. Identity -- A.2.Commutativity -- A.3. Associativity -- A.4. Distributivity -- A.5. Circularity -- B.1. Properties of the Fourier Transformation -- B.1.1. Inverse Fourier Transform -- B.1.2. Superposition -- B.1.3. Convolution and Multiplication -- B.1.4. Parseval's Theorem -- B.1.5. Time and Frequency Shift -- B.1.6. Symmetry -- B.1.7. Time and Frequency Scaling -- B.1.8. Derivatives -- B.2. Spectrum of Example Time Domain Signals.
505 0 _aContents note continued: B.2.1. Delta Function -- B.2.2. Constant -- B.2.3. Cosine -- B.2.4. Rectangular Window -- B.2.5. Delta Pulse -- B.3. Transformation of Sampled Time Signals -- B.4. Short Time Fourier Transform of Continuous Signals -- B.4.1. Window Functions -- B.5. Discrete Fourier Transform -- B.5.1. Window Functions -- B.5.2. Fast Fourier Transform -- C.1.Computation of the Transformation Matrix -- C.2. Interpretation of the Transformation Matrix -- D.1. Software Frameworks and Applications -- D.1.1. Marsyas -- D.1.2. CLAM -- D.1.3.jMIR -- D.1.4.CoMIRVA -- D.1.5. Sonic Visualiser -- D.2. Software Libraries and Toolboxes -- D.2.1. Feature Extraction -- D.2.2. Plugin Interfaces -- D.2.3. Other Software.
520 _a"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"-
650 0 _aComputational auditory scene analysis.
650 0 _aComputer sound processing.
650 0 _aContent analysis (Communication)
_xData processing.
650 4 _aComputational auditory scene analysis.
650 4 _aComputer sound processing.
650 4 _aContent analysis (Communication)
_xData processing.
650 7 _aCOMPUTERS
_xOptical Data Processing.
_2bisacsh
650 7 _aComputational auditory scene analysis.
_2fast
_0(OCoLC)fst01742148
650 7 _aComputer sound processing.
_2fast
_0(OCoLC)fst00872627
650 7 _aContent analysis (Communication)
_xData processing.
_2fast
_0(OCoLC)fst00876641
655 4 _aElectronic books.
776 0 8 _iPrint version:
_aLerch, Alexander.
_tIntroduction to audio content analysis.
_dHoboken, N.J. :
_bWiley
_z9781118266823
_w(DLC) 2012008107
_w(OCoLC)785390164
856 4 0 _uhttp://dx.doi.org/10.1002/9781118393550
_zWiley Online Library
994 _a92
_bDG1
999 _c19898
_d19857
526 _beee