Librería Portfolio

Features

Covers, in a comprehensive fashion, the foundations of music data analysis as well as advanced material
Contains all required introductory material in music, statistics and data mining
Shows various applications of music data analysis, including transcription and segmentation as well as chord and harmony, instrument and tempo recognition
Discusses implementation aspects of music data analysis, including architecture, user Interface and hardware
Summary

This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.



Table of Contents

K25499 TOC

Introduction

Background and Motivation

Content, Target Audience, Prerequisites, Exercises, and Complementary Material

Book Overview

Chapter Summaries

Course Examples

Authors and Editors

Bibliography

I Music and Audio

The Musical Signal - Physically and Psychologically

Introduction

The Tonal Quality: Pitch - The First Moment

Introduction

Pure and Complex Tones on a Vibrating String

Intervals and Musical Tone Height

Musical Notation and Naming of Pitches and Intervals

The Mel Scale

Fourier Transform

Correlation Analysis

Fluctuating Pitch and Frequency Modulation

Simultaneous Pitches

Other Sounds With and Without Pitch Percepts

Volume - The Second Moment

Introduction

The Physical Basis: Sound Waves in Air

Scales for the Subjective Perception of the Volume

Amplitude Modulation

Uncertainty Principle

Gabor Transform and Spectrogram

Formants, Vowels, and Characteristic Timbres of Voices and Instruments

Sound Fluctuations and Timbre

Physical Model for the Timbre of Wind Instruments

Duration - The Fourth Moment

Integration Times and Temporal Resolvability

Time Structure in Music: Rhythm and Measure

Wavelets and Scalograms

Further Reading

Exercises

Bibliography

Musical Structures and Their Perception

Introduction

Scales and Keys

Clefs

Diatonic and Chromatic Scales

Other Scales

Gestalt and Auditory Scene Analysis

Musical Textures from Monophony to Polyphony

Polyphony and Harmony

Dichotomy of Consonant and Dissonant Intervals

Consonant and Dissonant Intervals and Tone Progression

Elementary Counterpoint

Chords

Modulations

Time Structures of Music

Note Values

Measure

Meter

Rhythm

Elementary Theory of Form

Further Reading

Bibliography

Digital Filters and Spectral Analysis

Introduction

Continuous-Time, Discrete-Time, and Digital Signals

Discrete-Time Systems

Parametric LTI Systems

Digital Filters and Filter Design

The Discrete Fourier Transform

The Discrete Fourier Transform

Frequency Resolution and Zero Padding

Short-time Spectral Analysis

The Constant-Q Transform

Filter Banks for Short-time Spectral Analysis

Uniform Filter Banks

Nonuniform Filter Banks

The Cepstrum

Fundamental Frequency Estimation

Further Reading

Bibliography

Signal-Level Features

Introduction

Timbre Features

Time-Domain Features

Frequency-Domain Features

Mel Frequency Cepstral Coefficients

Harmony Features

Chroma Features

Chroma Energy Normalized Statistics

Timbre-Invariant Chroma Features

Characteristics of Partials

Rhythmic Features

Features for Onset Detection

Phase-Domain Characteristics

Fluctuation Patterns

Further Reading

Bibliography

Auditory Models

Introduction

Auditory Periphery

The Meddis Model of the Auditory Periphery

Outer and Middle Ear

Basilar Membrane

Inner Hair Cells

Auditory Nerve Synapse

Auditory Nerve Activity

Pitch Estimation Using Auditory Models

Autocorrelation Models

Pitch Extraction in the Brain

Further Reading

Bibliography

Digital Representation of Music

Introduction

From Sheet to File

Optical Music Recognition

abc Music Notation

Musical Instrument Digital Interface

MusicXML 3.0

From Signal to File

Pulse Code Modulation and Raw Audio Format

WAVE File Format

MP3 Compression

From File to Sheet

MusicTeX Typesetting

Transcription Tools

From File to Signal

Further Reading

Bibliography

Music Data: Beyond the Signal Level

Introduction

From the Signal Level to Semantic Features

Types of Semantic Features

Deriving Semantic Features

Discussion

Symbolic Features

Music Scores

Social Web

Social Tags

Shared Playlists

Listening Activity

Music Databases

Concluding Remarks

Bibliography

II Methods

Statistical Methods

Introduction

Probability

Theory

Empirical Analogues

Random Variables

Theory

Empirical Analogues

Characterization of Random Variables

Theory

Empirical Analogues

Important Univariate Distributions

Random Vectors

Theory

Empirical Analogues

Estimators of Unknown Parameters and their Properties

Testing Hypotheses on Unknown Parameters

Modeling of the Relationship between Variables

Regression

Time Series Models

Towards Smaller and Easier to Handle Models

Further Reading

Bibliography

Optimization

Introduction

Basic Concepts

Single-Objective Problems

Binary Feasible Sets

Continuous Feasible Sets

Compound Feasible Sets

Multi-Objective Problems

Further Reading

Bibliography

Unsupervised Learning

Introduction

Distance Measures and Cluster Distinction

Agglomerative Hierarchical Clustering

Agglomerative Hierarchical Methods

Ward Method

Visualization

Partition Methods

k-Means Methods

Self-Organizing Maps

Clustering Features

Independent Component Analysis

Further Reading

Bibliography

Supervised Classification

Introduction

Supervised Learning and Classification

Targets of Classification

Selected Classification Methods

Bayes and Approximate Bayes Methods

Nearest Neighbor Prediction

Decision Trees

Support Vector Machines

Ensemble Methods: Bagging

Neural Networks

Interpretation of Classification Results

Further Reading

Bibliography

Evaluation

Introduction

Resampling

Resampling Methods

Hold-Out

Cross-Validation

Bootstrap

Subsampling

Properties and Recommendations

Evaluation Measures

Loss Based Performance

Confusion Matrix

Common Performance Measures Based on the Confusion Matrix

Measures for Imbalanced Sets

Evaluation of Aggregated Predictions

Measures Beyond Classification Performance

Hyperparameter Tuning: Nested Resampling

Test