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
MUSIC AND AUDIO. Introduction. The Musical Signal - Physically and Psychologically. Musical Structures and Their Perception. Digital Signal Processing. Digital Representation of Music. Signal-level Features. METHODS. Foundations of Statistics. Optimization. Unsupervised Classification. Supervised Classification. Evaluation. Feature Processing. Feature Selection. APPLICATIONS. Transcription. Segmentation. Instrument Recognition. Chord and Harmony Recognition. Tempo Recognition. Emotions. Structuring Of Music Collections. Music Recommendation. Automatic Composition. IMPLEMENTATION. Architecture. User Interaction. Hardware.
Dietmar Jannach, Günter Rudolphm and Igor Vatolkin are affiliated with the Department of Computer Science, TU Dortmund University, Germany
Claus Weihs is affiliated with the Department of Statistics at TU Dortmund University, Germany
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