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These video lectures relate to edition 1 of the book, meaning that they will be differently structured and differ in content details. The lectures are an introduction to the software-based analysis of digital music signals (Music Information Retrieval) for students with existing background in audio processing. It covers the basic approaches for audio content analysis and provides students with the necessary algorithmic background to approach this class of problems. Topics include, for example, pitch tracking, beat tracking, audio feature extraction, and genre classification.

prerequisites

Prior coursework in signal processing is expected – the fundamentals module of the class will introduce concepts in detail. Familiarity with and access to Matlab or Octave is required.

learning outcomes

After successful completion of this class, the students will be able to

  • summarize and explain baseline approaches to typical tasks in Music Information Retrieval
  • describe and apply evaluation methods and metrics for audio content analysis systems,
  • implement audio content analysis systems in Matlab.

course outline

chapter 1: introduction

chapter 2: fundamentals

chapter 3: instantaneous features

chapter 4: intensity & loudness

chapter 5: tonal analysis

chapter 6: temporal analysis

chapter 7: audio alignment

chapter 8: music genre classification, similarity, mood

chapter 9: audio fingerprinting

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Book Cover Image: An Introduction to Audio Content Analysis @ IEEE







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alexander lerch

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