Presentation is loading. Please wait.

Presentation is loading. Please wait.

Musical Analysis using statistical methods 20020030 권상일.

Published byAlberta Kelly Modified over 9 years ago

Similar presentations

Presentation on theme: "Musical Analysis using statistical methods 20020030 권상일."— Presentation transcript:

1 Musical Analysis using statistical methods 20020030 권상일

2 Contents 1. Overview 2. MIDI 3. Theories 4. Samples 5. Results 6. Limits 7. Conclusion 8. Reference

3 1. Overview What I want to do is…  Analyze music with statistical approach.  Search or define quantity that shows characteristics of music.  Find the factors that determine the BEAUTY of famous songs.

4 2. MIDI (1) Musical Instrument Digital Interface Digitalized Score  Time, channel, note, volume, instruments, and various effects… Table of few channel voice messages Channel Voice Messages Status D7----D0 Data Byte(s) D7----D0 Description 1000nnnn 0kkkkkkk 0vvvvvvv Note Off event. (kkkkkkk) is the key (note) number. (vvvvvvv) is the velocity. 1001nnnn 0kkkkkkk 0vvvvvvv Note On event. (kkkkkkk) is the key (note) number. (vvvvvvv) is the velocity.

5 2. MIDI (2) Table of MIDI Note Numbers Octave Number Note Numbers CC#DD#EFF#GG#AA#B 01234567891011 0121314151617181920212223 1242526272829303132333435 2363738394041424344454647 3484950515253545556575859 4606162636465666768697071 5727374757677787980818283 6848586878889909192939495 796979899100101102103104105106107 8108109110111112113114115116117118119 9120121122123124125126127

6 3. Theories (1) 1/f law (musical Zipf’s law)  Almost every music have 1/f dependence.  Frequency spectrum  Pitch interval distribution Scatter diagram  It shows how strongly or weakly related one piece of data is to the previous one.  The x-axis is labeled n and the y-axis is n-1

7 3. Theories (2) Fractal dimension  Scatter Diagram’s fractal dimension is given by

8 3. Theories (3) Entropy  Treat each pitches as accessible states and the number of appearance as probabilities. Then  High entropy : there are many chromatic notes… Fractal dimension and entropy tells us  Degree of correlation and ratio of chromatic scale

9 4. Samples (1) Why many Beatles?  Lennon and McCartney’s songs have SIMPLE and VARIOUS style.  They are so FAMOUS! Why Debussy?  His melody line was very UNUSUAL form for that time. Why Bach?  Many people says, “Bach’s music has esthetical BEAUTY!” ComposerTitleTonic J. S. Bach Cello Suite No. 1 in G major - BWV 1007, Prelude43 (G major) Cello Suite No. 3 in C major - BWV 1009, Courante48 (C major) Cello Suite No. 6 in D major - BWV 1012, Courante50 (D major) The Art of Fugue - BWV 1080, Contrapunctus I62 (D minor) C. Debussy Clair de lune73 (C# major) Prelude a l'Apres-Midi d'un Faune71 (B major) J. Lennon (The Beatles) Across The Universe74 (D major) Girl72 (C minor) Julia60 (C major) Norwegian Wood64 (E major) Nowhere Man64 (E major) Strawberry Fields Forever70 (A# major) P. McCartney (The Beatles) And I Love Her68 (G# minor) Here, There And Everywhere67 (G major) In My Life69 (A major) Let It Be72 (C major) Michelle62 (D minor) Penny Lane72 (Cmajor) Yesterday65 (F minor)

10 4. Samples (2)

11 4. Samples (3) Programs  Note counts  Deviation  Interval counts  Interval distribution (scatter diagram)  Pitch counts  Fractal dimension  Entropy

12 5. Results – Zipf’s Law (1) Well-known factors satisfy Zifp’s law  Frequency spectrum  Pitch interval distribution  Etc…

13 Bach – CS No. 1 in G major - BWV 1007, Prelude Debussy - Prelude a l'Apres-Midi d'un Faune Lennon - Nowhere ManMcCartney - Yesterday

14 Bach – CS No. 1 in G major - BWV 1007, Prelude Debussy - Prelude a l'Apres-Midi d'un Faune Lennon - Nowhere ManMcCartney - Yesterday

15 5. Results – Scatter Diagrams (1) SD shows how close the notes are. How can we know? Look at 1/f β !  0 < β < 0.5 : white noise, nearly random  0.5 < β < 1 : pink noise, most songs are in here!  1.5 < β < 2 : brown noise, too correlated Compare with y=x graph.  Near : repetitious  Far : varied

16 Debussy – Clair de lune (-1.3)Bach – AF BWV 1080 Contrapunctus I (2) (-1.6) Lennon – Strawberry Field Forever (-1.2)McCartney – Yesterday (-1.3)

17 5. Results – Relative Pitch (1) Relative Pitch shows…  How chromatic a passage is? Why we observe relative pitch?  To calculate entropy  Most of people recognize tonic, major third, perfect fourth, and perfect fifth better than other pitches  To give the answer : What makes comfortable music be COMFORTABLE?

18 Bach - Suite No. 1 in G major - BWV 1007, Prelude Debussy - Prelude a l'Apres-Midi d'un Faune Lennon – Norwegian WoodMcCartney – Let it be

19 5. Results – Dimension & Entropy (1) ComposerTitleDimensionEntropy J. S. Bach Cello Suite No. 1 in G major - BWV 1007, Prelude0.27372.163 Cello Suite No. 3 in C major - BWV 1009, Courante0.27282.209 Cello Suite No. 6 in D major - BWV 1012, Courante0.037142.098 The Art of Fugue - BWV 1080, Contrapunctus I (2)0.27032.186 C. Debussy Clair de lune0.087222.160 Prelude a l'Apres-Midi d'un Faune0.26802.207 J. Lennon (The Beatles) Across The Universe0.073421.793 Girl0.20751.804 Julia0.23281.695 Norwegian Wood0.057742.042 Nowhere Man0.096321.854 Strawberry Fields Forever0.17571.943 P. McCartney (The Beatles) And I Love Her0.033561.893 Here, There And Everywhere0.21272.029 In My Life0.057741.748 Let It Be0.076001.601 Michelle0.24741.803 Penny Lane0.24271.919 Yesterday0.060151.937

20 5. Results – Dimension & Entropy (2) NumberTitleDimension 1Bach - Cello Suite No. 1 in G major - BWV 1007, Prelude0.2737 2Bach - Cello Suite No. 3 in C major - BWV 1009, Courante0.2728 3Bach - The Art of Fugue - BWV 1080, Contrapunctus I (2)0.2703 4Debussy - Prelude a l'Apres-Midi d'un Faune0.268 5McCartney – Michelle0.2474 6McCartney - Penny Lane0.2427 7Lennon – Julia0.2328 8McCartney - Here, There And Everywhere0.2127 9Lennon – Girl0.2075 10Lennon - Strawberry Fields Forever0.1757 11Lennon - Nowhere Man0.09632 12Debussy - Clair de lune0.08722 13McCartney - Let It Be0.076 14Lennon - Across The Universe0.07342 15McCartney – Yesterday0.06015 16Lennon - Norwegian Wood0.05774 17McCartney - In My Life0.05774 18Bach - Cello Suite No. 6 in D major - BWV 1012, Courante0.03714 19McCartney - And I Love Her0.03356

21 5. Results – Dimension & Entropy (3) NumberTitleEntropy 1Bach - Cello Suite No. 3 in C major - BWV 1009, Courante2.209 2Debussy - Prelude a l'Apres-Midi d'un Faune2.207 3Bach - The Art of Fugue - BWV 1080, Contrapunctus I (2)2.186 4Bach - Cello Suite No. 1 in G major - BWV 1007, Prelude2.163 5Debussy - Clair de lune2.16 6Bach - Cello Suite No. 6 in D major - BWV 1012, Courante2.098 7Lennon - Norwegian Wood2.042 8McCartney - Here, There And Everywhere2.029 9Lennon - Strawberry Fields Forever1.943 10McCartney - Yesterday1.937 11McCartney - Penny Lane1.919 12McCartney - And I Love Her1.893 13Lennon - Nowhere Man1.854 14Lennon - Girl1.804 15McCartney - Michelle1.803 16Lennon - Across The Universe1.793 17McCartney - In My Life1.748 18Lennon - Julia1.695 19McCartney - Let It Be1.601

22 5. Results – Dimension & Entropy (4) ComposerBachDebussyLennonMcCartney Dimension0.15270.17760.14060.1329 Entropy2.1642.1841.8551.847 The entropy of impressionist Debussy is higher than that of baroque composer Bach. Easy-listening pop song has very low entropy  It is a SONG.  Bach and Debussy’s sample music is orchestra pieces.

23 6. Limits (1) Statistical approach  Notes are NOT INDEPENDENT particles. Complexity  Changing key makes entropy higher.  Polyphony music is pretty hard… Dimension  It’s not easy that consider other factors (such as volume, rhythm, etc.) Various composition goal  There are so many genre! (such as rap)

24 6. Limits (2) Catching the exact key is not so easy… Example (McCartney – Yesterday)

25 7. Conclusion Statistical approach can give us MOST OBJECTIVE data. So it can be a good music analysis in spite of many limits. Beauty of music is dependent on  1/f (of course!)  Tonic, major third, perfect fourth, perfect fifth  But they are just NECESSARY condition. So, what can we do with that methods?  Give a quantitative value of certain music  Artificial compose

26 8. Reference 이석원, 음악심리학, 심설당, 1994. Madden, C. "Fractals in Music: Introductory Mathematics for Musical Analysis", High Art Press, 1999. Manaris B., McCormick, C. and Purewal, T. "Can Beautiful Music be Recognized by Computers? Nature, Music, and the Zipf-Mandelbrot Law," Technical Report CoC/CS TR#2002-7-1, March 2002. http://www.midiox.com/ http://www.csw2.co.uk/tech/midi2.htm

Download ppt "Musical Analysis using statistical methods 20020030 권상일."

Similar presentations

The Pythagorean perception of music Music was considered as a strictly mathematical discipline, handling with number relationships, ratios and proportions.

The Pythagorean perception of music Music was considered as a strictly mathematical discipline, handling with number relationships, ratios and proportions.
For those who have never played an instrument

For those who have never played an instrument
The Beatles The Beatles are the most famous group of the 20th century. They influenced the style of all the young people in their time and the modern.

The Beatles The Beatles are the most famous group of the 20th century. They influenced the style of all the young people in their time and the modern.
Chi-Square Test A fundamental problem is genetics is determining whether the experimentally determined data fits the results expected from theory (i.e.

Chi-Square Test A fundamental problem is genetics is determining whether the experimentally determined data fits the results expected from theory (i.e.
Statistics 100 Lecture Set 7. Chapters 13 and 14 in this lecture set Please read these, you are responsible for all material Will be doing chapters 15-19.

Statistics 100 Lecture Set 7. Chapters 13 and 14 in this lecture set Please read these, you are responsible for all material Will be doing chapters
GROUP MEMBERS-  ZION- PROJECT LEADER  TYRESE-CHIEF RESEARCHER  MUSKAN-COMMUNICATIONS DIRECTOR  GHAZAL-DIGITAL ENGINEER.

GROUP MEMBERS-  ZION- PROJECT LEADER  TYRESE-CHIEF RESEARCHER  MUSKAN-COMMUNICATIONS DIRECTOR  GHAZAL-DIGITAL ENGINEER.
BHS 204-01 Methods in Behavioral Sciences I April 18, 2003 Chapter 4 (Ray) – Descriptive Statistics.

BHS Methods in Behavioral Sciences I April 18, 2003 Chapter 4 (Ray) – Descriptive Statistics.
Chapter 9 Baroque Instrumental Music Fugue. Key Terms Fugue Fugue subject Expositions Subject entries Episodes Contrapunctus Free and learned fugues Fugato.

Chapter 9 Baroque Instrumental Music Fugue. Key Terms Fugue Fugue subject Expositions Subject entries Episodes Contrapunctus Free and learned fugues Fugato.
QUANTITATIVE DATA ANALYSIS

QUANTITATIVE DATA ANALYSIS
Timbre (pronounced like: Tamber) pure tones are very rare a single note on a musical instrument is a superposition (i.e. several things one on top of.

Timbre (pronounced like: Tamber) pure tones are very rare a single note on a musical instrument is a superposition (i.e. several things one on top of.
Johann Sebastian Bach (1685 –1750) German Organ virtuoso 1717: Named Kapellmeister of the Court Cothen Not famous or recognized in his day - Was an acclaimed.

Johann Sebastian Bach (1685 –1750) German Organ virtuoso 1717: Named Kapellmeister of the Court Cothen Not famous or recognized in his day - Was an acclaimed.
Class 5: Thurs., Sep. 23 Example of using regression to make predictions and understand the likely errors in the predictions: salaries of teachers and.

Class 5: Thurs., Sep. 23 Example of using regression to make predictions and understand the likely errors in the predictions: salaries of teachers and.
Introduction to Econometrics The Statistical Analysis of Economic (and related) Data.

Introduction to Econometrics The Statistical Analysis of Economic (and related) Data.
Chapter 14 Analyzing Quantitative Data. LEVELS OF MEASUREMENT Nominal Measurement Nominal Measurement Ordinal Measurement Ordinal Measurement Interval.

Chapter 14 Analyzing Quantitative Data. LEVELS OF MEASUREMENT Nominal Measurement Nominal Measurement Ordinal Measurement Ordinal Measurement Interval.
BHS 204-01 Methods in Behavioral Sciences I April 21, 2003 Chapter 4 & 5 (Stanovich) Demonstrating Causation.

BHS Methods in Behavioral Sciences I April 21, 2003 Chapter 4 & 5 (Stanovich) Demonstrating Causation.
PH 105 Dr. Cecilia Vogel Lecture 14. OUTLINE  units of pitch intervals  cents, semitones, whole tones, octaves  staves  scales  chromatic, diatonic,

PH 105 Dr. Cecilia Vogel Lecture 14. OUTLINE  units of pitch intervals  cents, semitones, whole tones, octaves  staves  scales  chromatic, diatonic,
Music Appreciation Grade 12 Mr. Gribble The Modern Era  It is a blend of many types of music.  It blends forms of popular music such as jazz, blues,

Music Appreciation Grade 12 Mr. Gribble The Modern Era  It is a blend of many types of music.  It blends forms of popular music such as jazz, blues,
Statistics - Descriptive statistics 2013/09/23. Data and statistics Statistics is the art of collecting, analyzing, presenting, and interpreting data.

Statistics - Descriptive statistics 2013/09/23. Data and statistics Statistics is the art of collecting, analyzing, presenting, and interpreting data.
Chi-Square Test A fundamental problem in genetics is determining whether the experimentally determined data fits the results expected from theory (i.e.

Chi-Square Test A fundamental problem in genetics is determining whether the experimentally determined data fits the results expected from theory (i.e.
Information Theory and Security Prakash Panangaden McGill University First Canada-France Workshop on Foundations and Practice of Security Montréal 2008.

Information Theory and Security Prakash Panangaden McGill University First Canada-France Workshop on Foundations and Practice of Security Montréal 2008.

Similar presentations

Ads by Google