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Aspects of Music Lecture Piece of music Music Processing Chord Recognition Rhythm Meinard Müller Melody International Audio Laboratories Erlangen meinard.mueller@audiolabs-erlangen.de Harmony Harmony: The Basis of Music Musical Chords Pachelbel’s Canon Combination of three or more tones which sound simultaneously Chord classes – Triads including major, minor, diminished, augmented chords – Many other more complex chords such as seventh chords Here: focus on major and minor triads Coversong Die Eine (Die Firma) Musical Chords Musical Chords The C major chord The C minor chord Derived from the C major scale Derived from the C minor scale C ---- the root C ---- the root E ---- the (major)third Eb---- the (minor)third G ---- the fifth G ---- the fifth Musical Chords Chord Recognition Structure of the 24 major/minor chords Development of automatic methods for the harmonic analysis of audio data Applications in the field of music information 01234567891011 retrieval: CC#DD#EFF#GG#AA#B – music segmentation C major – cover song identification – audio matching C minor – music structure analysis – … Chord Recognition Chord Recognition Signal Result Signal Feature Classification Result Extraction Segmentation Chroma features Pattern matching Chord label assignment C F G C Type Template Resolution Gaussian Compression Hidden Markov Models Smoothing Graphical Models Chord Recognition Baseline Method for Chord Recognition Given: Audio file Chord templates 24 major/minor chords Output: Segmentation and chord labeling C C# D D# …… C C# …… major major major major minor minor B 0 0 0 0 …… 0 0 …… A# 0 0 0 1 …… 0 0 …… A 0 0 1 0 …… 0 0 …… G# 0 1 0 0 …… 0 1 …… G 1 0 0 1 …… 1 0 …… F# 0 0 1 0 …… 0 0 …… C A:min E:min FC FCA:min E:min G G G F 0 1 0 0 …… 0 0 …… E 1 0 0 0 …… 0 1 …… D# 0 0 0 1 …… 1 0 …… D 0 0 1 0 …… 0 0 …… CGA:minE:min G C# 0 1 0 0 …… 0 1 …… F C FG F CF C 1 0 0 0 …… 1 0 …… Baseline Method for Chord Recognition Baseline Method for Chord Recognition Chord templates 24 major/minor chords 24 chord templates Chromafeature (12 major, 12 minor) extraction (framewise) Chroma Chord labels Baseline Method for Chord Recognition Baseline Method for Chord Recognition 24 chord templates Chromafeature 24 chord templates Chromafeature (12 major, 12 minor) extraction (framewise) (12 major, 12 minor) extraction (framewise) Compute for each frame the distance of Compute for each frame the distance of the feature vector to the 24 templates the feature vector to the 24 templates Selected chord according to template with minimal distance to respective feature vector Problems in Chord Recognition Problems in Chord Recognition Problem: Transitions between subsequent chord Problem: Monphonic musical passages Example: Chopin Mazurka Op. 68 No.3 Example: Excerpt of Wagner’s Meistersinger Chromagram Correct 1 B False positive A# 0.9 A 0.8 False negative G# 0.7 G 0.6 F# 0.5 F E 0.4 D# 0.3 D 0.2 C# 0.1 C 0 0 10 20 30 40 50 60 Problems in Chord Recognition Problems in Chord Recognition Problem: Frame-wise chord analysis may not be meaningful Problem: Ambiguity of chords Example: Bach: Prelude C major, BWV 846 A minor C major E minor A C C E E E Problem: Broken chords G G B → Measure-wise chord analysis necessary Problems in Chord Recognition Problems in Chord Recognition Problem: Reduction to the 24 major/minor chords makes Problem: Tuning problems the recognition of more complex chords difficult/impossible! Example: Excerpt of Wagner’s Meistersinger Example: Prelude C major, BWV 846, mm.19-25 Chromagram (from MIDI) 1 B 0.9 A# A 0.8 G# 0.7 G 0.6 F# 0.5 F 0.4 E 0.3 D# D 0.2 C# 0.1 C 0 0 10 20 30 40 50 60 Problems in Chord Recognition Problems in Chord Recognition Problem: Tuning problems Problem: Tuning problems Example: Excerpt of Wagner’s Meistersinger Example: Excerpt of Wagner’s Meistersinger Chromagram (from MIDI) Problem: Chromagram (from MIDI) Problem: 1 Audio is tuned more than 1 Audio is tuned more than B B A# 0.9 half a semi-tone upwards 0.9 half a semi-tone upwards A# A 0.8 A 0.8 G# 0.7 G# 0.7 Solution: G 0.6 G 0.6 F# F# Adjust frequency binning 0.5 0.5 F F E 0.4 0.4 when computing pitch E D# 0.3 D# 0.3 features. D 0.2 D 0.2 C# 0.1 C# 0.1 C C 0 0 0 10 20 30 40 50 60 0 10 20 30 40 50 60
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