Introduction Meinard Mller International Audio Laboratories - - PowerPoint PPT Presentation

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Introduction Meinard Mller International Audio Laboratories - - PowerPoint PPT Presentation

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Lecture Music Processing Introduction Meinard Mller International Audio Laboratories Erlangen meinard.mueller@audiolabs-erlangen.de Music Music Information Retrieval (MIR) MusicXML (Text) Sheet Music (Image) CD / MP3 (Audio) Dance /

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Music Processing Meinard Müller

Lecture

Introduction

International Audio Laboratories Erlangen meinard.mueller@audiolabs-erlangen.de

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Music

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Music Information Retrieval (MIR)

Sheet Music (Image) CD / MP3 (Audio) MusicXML (Text) Music Film (Video) Dance / Motion (Mocap) MIDI Music Literature (Text) Singing / Voice (Audio)

Music

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Music Information Retrieval (MIR) Music

Musicology Library Sciences User Interfaces Signal Processing Machine Learning Information Retrieval

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Piano Roll Representation

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Player Piano (1900)

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Time Pitch J.S. Bach, C-Major Fuge (Well Tempered Piano, BWV 846)

Piano Roll Representation (MIDI)

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Query: Goal: Find all occurrences of the query

Piano Roll Representation (MIDI)

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Matches:

Piano Roll Representation (MIDI)

Query: Goal: Find all occurrences of the query

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Music Retrieval

Query Database Hit Bernstein (1962) Beethoven, Symphony No. 5 Beethoven, Symphony No. 5:

  • Bernstein (1962)
  • Karajan (1982)
  • Gould (1992)
  • Beethoven, Symphony No. 9
  • Beethoven, Symphony No. 3
  • Haydn Symphony No. 94

Audio-ID Version-ID Category-ID

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Music Synchronization: Audio-Audio

Beethoven’s Fifth

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Music Synchronization: Audio-Audio

Time (seconds)

Beethoven’s Fifth Orchester (Karajan) Piano (Scherbakov)

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Music Synchronization: Audio-Audio

Time (seconds)

Beethoven’s Fifth Orchester (Karajan) Piano (Scherbakov)

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Application: Interpretation Switcher

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Music Synchronization: Image-Audio

Image Audio

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Music Synchronization: Image-Audio

Image Audio

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How to make the data comparable?

Image Audio

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How to make the data comparable?

Image Audio

Image Processing: Optical Music Recognition

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How to make the data comparable?

Image Audio

Audio Processing: Fourier Analysis Image Processing: Optical Music Recognition

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How to make the data comparable?

Image Audio

Audio Processing: Fourier Analysis Image Processing: Optical Music Recognition

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Application: Score Viewer

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Music Structure Analysis

Example: Brahms Hungarian Dance No. 5 (Ormandy)

Time (seconds)

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Music Structure Analysis

Example: Brahms Hungarian Dance No. 5 (Ormandy)

Time (seconds)

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Music Structure Analysis

Example: Brahms Hungarian Dance No. 5 (Ormandy)

Time (seconds)

A1 A2 A3 B1 B2 B3 B4 C

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Tempo Estimation and Beat Tracking

Time (seconds)

Example: Queen – Another One Bites The Dust Basic task: “Tapping the foot when listening to music’’

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Time (seconds)

Tempo Estimation and Beat Tracking

Example: Queen – Another One Bites The Dust Basic task: “Tapping the foot when listening to music’’

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Tempo Estimation and Beat Tracking

Light effects Music recommendation DJ Audio editing

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Why is Music Processing Challenging?

Chopin, Mazurka Op. 63 No. 3 Example:

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Why is Music Processing Challenging?

  • Waveform

Chopin, Mazurka Op. 63 No. 3 Example:

Amplitude Time (seconds)

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Why is Music Processing Challenging?

  • Waveform / Spectrogram

Chopin, Mazurka Op. 63 No. 3 Example:

Frequency (Hz) Time (seconds)

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Why is Music Processing Challenging?

  • Waveform / Spectrogram
  • Performance

– Tempo – Dynamics – Note deviations – Sustain pedal

Chopin, Mazurka Op. 63 No. 3 Example:

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Why is Music Processing Challenging?

  • Waveform / Spectrogram
  • Performance

– Tempo – Dynamics – Note deviations – Sustain pedal

  • Polyphony

Chopin, Mazurka Op. 63 No. 3 Example:

Main Melody Accompaniment Additional melody line

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Audio Identification Structure Analysis Fourier Transform Audio Features

Music Processing

Music Synchronization Tempo and Beat Tracking Audio Decomposition

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Book: Fundamentals of Music Processing

Meinard Müller Fundamentals of Music Processing Audio, Analysis, Algorithms, Applications 483 p., 249 illus., hardcover ISBN: 978-3-319-21944-8 Springer, 2015 Accompanying website: www.music-processing.de

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Book: Fundamentals of Music Processing

Meinard Müller Fundamentals of Music Processing Audio, Analysis, Algorithms, Applications 483 p., 249 illus., hardcover ISBN: 978-3-319-21944-8 Springer, 2015 Accompanying website: www.music-processing.de