Analytical uses of Humdrum Tools

Slides:



Advertisements
Similar presentations
AP Music Theory Ms. Friedrichs.
Advertisements

MusicXml: Symbolic Music Interchange Format Carmine Casciato MUMT 611 Thursday, January 27th, 2005 Carmine Casciato MUMT 611 Thursday, January 27th, 2005.
Humdrum - Introduction What is Humdrum? A set of general-purpose music software tools, but free Encode, manipulate, and output a wide variety of musically-pertinent.
Schenker’s late theory in overview
Guerino Mazzola U & ETH Zürich Internet Institute for Music Science architecture du livre „The Topos of Music“
Outline Introduction Music Information Retrieval Classification Process Steps Pitch Histograms Multiple Pitch Detection Algorithm Musical Genre Classification.
Musical Similarity: More perspectives and compound techniques CS 275B/Music 254.
Rhythmic Similarity Carmine Casciato MUMT 611 Thursday, March 13, 2005.
Melodic Similarity CS 275B/Music 254. "Natural history" of similarity  Concept of similarity fundamental to organization of most art music  Types of.
Functional Music Interim Presentation Simon McNeilly Supervisors Dr. Lloyd Allison Dr. Jon McCormack.
8 Introduction to Humdrum Mus 253/CS 275A Stanford University Winter Quarter.
From Discrete Mathematics to AI applications: A progression path for an undergraduate program in math Abdul Huq Middle East College of Information Technology,
Presented To: Madam Nadia Gul Presented By: Bi Bi Mariam.
Computer Science Universiteit Maastricht Institute for Knowledge and Agent Technology Data mining and the knowledge discovery process Summer Course 2005.
Transforming XML Into Music Notation Baron Schwartz, Computer Science Perry Roland, Digital Library Worthy Martin, Computer Science.
CHARM Advisory Board Meeting Institute for Historical Research, School of Advanced Study, UL Senate House, London 12 Dec 2006 Craig Stuart Sapp Centre.
Content Visualization in a Digital Music Library Eric J. Isaacson Assoc. Prof. of Music Theory Indiana University School of Music This material is based.
JSymbolic and ELVIS Cory McKay Marianopolis College Montreal, Canada.
Introduction of Humdrum Music 253/CS 275A Stanford University.
Introduction to algorithmic models of music cognition David Meredith Aalborg University.
Last Words COSC Big Data (frameworks and environments to analyze big datasets) has become a hot topic; it is a mixture of data analysis, data mining,
HANA HARRISON CSE 435 NOVEMBER 19, 2012 Music Composition.
August 12, 2004IAML - IASA 2004 Congress, Olso1 Music Information Retrieval, or how to search for (and maybe find) music and do away with incipits Michael.
JSymbolic Cedar Wingate MUMT 621 Professor Ichiro Fujinaga 22 October 2009.
Music Information Retrieval -or- how to search for (and maybe find) music and do away with incipits Michael Fingerhut Multimedia Library and Engineering.
ENOMA - European Network of Online Musical Archives ENOMA Workshop – The Grieg Academy, UiB 26 May 2006 Leif Arne Rønningen and Lars Erik Løvhaug NTNU.
Aspects of Rhythm and Meter Music 254. Regularity vs Irregularity  Meter  Ordinary meters as notated  Ordinary meters as sounded/heard  Unmeasured.
Tonal Space and the Human Mind By P. Janata Presented by Deepak Natarajan.
CODES FOR DATA ARCHIVING, INTERCHANGE, AND ANALYSIS: MUSEDATA Music 253/CS 275A Stanford University.
What is musical information? Music 253/CS 275A Topic 1A Stanford University.
Melodic Search: Strategies and Formats CS 275B/Music 254.
Symbolic Musical Analysis CS 275B/Music 254. Practicalities CS 275B2013 Eleanor Selfridge-Field2.
Using Musical Information Music 253/CS 275A 1B Stanford University.
The Mazurka Project Science and Music Seminar University of Cambridge 28 Nov 2006 Craig Stuart Sapp Centre for the History and Analysis of Recorded Music.
An Introduction to SCORE
Using Musical Information: Query, Analysis, and Style Simulation Mus 254/CS 275B/SSP 253b Stanford University Spring Quarter.
1/12/ Multimedia Data Mining. Multimedia data types any type of information medium that can be represented, processed, stored and transmitted over.
Issues in Automatic Musical Genre Classification Cory McKay.
College of Computer Science, SCU Computer English Lecture 1 Computer Science Yang Ning 1/46.
Music 254 Stanford University Eleanor Selfridge-Field2  Details of individual selections  Seek precise match (Themefinder)  Features in-the-round.
Alex Stabile. Research Questions: Could a computer learn to distinguish between different composers? Why does music by different composers even sound.
Symbolic Musical Analysis CS 275B/Music 254. Practicalities CS 275B2016 Eleanor Selfridge-Field2.
Pattern Recognition. What is Pattern Recognition? Pattern recognition is a sub-topic of machine learning. PR is the science that concerns the description.
Harmonic Models CS 275B/Music 254.
Aspects of Rhythm and Meter Music 254. Regularity vs Irregularity  Meter  Ordinary meters as notated  Ordinary meters as sounded/heard  Unmeasured.
Computer-Generated Sound Final Project
Musical Similarity: More perspectives and compound techniques
Authoring the AP Music Theory Exam: Consultation and Collaboration
Carmine Casciato MUMT 611 Thursday, March 13, 2005
Musical Information 1B Music 253/CS 275A Stanford University
Codes for data archiving, interchange, and analysis
School of Information Management Nanjing University China
Craig Stuart Sapp ICMC 2001 Havana, Cuba
FUNDAMENTALS OF MACHINE LEARNING AND DEEP LEARNING
Carmine Casciato MUMT 611 Thursday, March 13, 2005
Aspects of Music Information Retrieval
From Experiments in Musical Intelligence to Emily Howell
Welcome to Music Class! Mrs. Sandor. Welcome to Music Class! Mrs. Sandor.
Fine Arts section 1 pg.7-20 By david steen.
Integrating Segmentation and Similarity in Melodic Analysis
Introduction to Humdrum
Craig Stuart Sapp Yi-Wen Liu Eleanor Selfridge-Field ISMIR 2004
Symbolic Musical Analysis
Theories of meter, rhythm, and form
Melodic Similarity CS 275B/Music 254.
MusicXml: Symbolic Music Interchange Format
Pitch Spelling Algorithms
Word representations David Kauchak CS158 – Fall 2016.
SDSEN: Self-Refining Deep Symmetry Enhanced Network
Presentation transcript:

Analytical uses of Humdrum Tools Musical Information 1B Analytical uses of Humdrum Tools Music 253/CS 275A Stanford University

Traditional categories of music analysis Musical Information 1B Traditional categories of music analysis Traditional means of analysis Harmony Counterpoint Melody Rhythm Feature sets CS 275A/Music 253 2019 Eleanor Selfridge-Field

Traditional categories of music analysis Musical Information 1B Traditional categories of music analysis Traditional means of analysis Harmony Counterpoint Melody Rhythm Feature sets Humdrum = Toolset **kern = encoding format CS 275A/Music 253 2019 Eleanor Selfridge-Field

>>Manual processes in music analysis Riemann analysis Schenkarian analysis Blair Johnson, MTO (2012) Root analysis CS 275A/Music 253 2019 Eleanor Selfridge-Field

Perspectives on music analysis: 1-2 Traditional (theoretical, historical) means of analysis Harmony Counterpoint Melody Rhythm Statistical (systematic) approaches Audio-based analysis Feature sets: Results related to score Feature sets: results reported in tables, charts, graphs Disembodied information about music CS 275A/Music 253 2019 Eleanor Selfridge-Field

More approaches to analysis Procedures imported from other disciplines Often procedural or structural Borrowed from Linguistics Mathematics Computer science Engineering Cognitive and perceptual studies Performance-based analysis Data visualization CS 275A/Music 253 2019 Eleanor Selfridge-Field

Other legitimate projects Data translation, enrichment Linking symbolic data with MIDI, audio, structured data Style evaluation generation as proof of general concept Attribution studies (e.g. Josquin Research Project) Deep-learning/convolutional-network (AI) analysis CS 275A/Music 253 2019 Eleanor Selfridge-Field

Sample Projects, Random Order CS 275A/Music 253 2019 Eleanor Selfridge-Field

Algorithmic generation: 12-bar blues Francesco Giomi, c. 1988 Is repertory highly patterned? CS 275A/Music 253 2019 Eleanor Selfridge-Field

Phrase families (centonization) Panos Mavromatis (2006) N.B. Lerdahl-Jackendoff touch Linguistic orientation CS 275A/Music 253 2019 Eleanor Selfridge-Field

Hierarchical systems: Lerdahl-Jackendoff Generative theories of musical grammar (1984) CS 275A/Music 253 2019 Eleanor Selfridge-Field

Linear systems (species counterpoint) Several systems Pedagogical orientation CS 275A/Music 253 2019 Eleanor Selfridge-Field

Imitative systems (18th-century counterpoint) Timothy Smith, NAU Music-theory applications CS 275A/Music 253 2019 Eleanor Selfridge-Field

Generative chorale variations Dominik Hörnel (2005): Pachelbel Keyboard elaboration generated from chorale melody Chorale elaboration CS 275A/Music 253 2019 Eleanor Selfridge-Field

Rhythm, Meter, Tempo (performance) Comparative performance analysis Simon Dixon, Gerhard Widmer, Walter Göbl (2004) CS 275A/Music 253 2019 Eleanor Selfridge-Field

Computation perception Gerhard Widmer, Motherboard (2016) CS 275A/Music 253 2019 Eleanor Selfridge-Field

Geospatial mapping of musical features Bret Aarden (1998), from EsAC data Minor mode Triple meter CS 275A/Music 253 2019 Eleanor Selfridge-Field

2019 Eleanor Selfridge-Field Tabla drumming Parag Chordia: bol processor (2006) Non-Western repertories CS 275A/Music 253 2019 Eleanor Selfridge-Field

Haydn-Mozart Quartet Quiz (machine learning/information theory) Yi-Wen Liu, C. Sapp (2002-04) -entropy study (EE) [qq.themefinder.org] CS 275A/Music 253 2019 Eleanor Selfridge-Field

Themefinder (melodic search) Huron, Kornstädt, Sapp, et al. (1996) themefinder.org Similarity studies CS 275A/Music 253 2019 Eleanor Selfridge-Field

Computer methodologies in music search Musical Information 1B Computer methodologies in music search Music geohash Counterpoint/surfacing crawling Musical structure discovery via deep-learning algorithms (2016) Currently runs ETLeap (data extraction, transformation, loading) CS 275A/Music 253 2019 Eleanor Selfridge-Field

Melodic search in big data Sapp, Liu, Selfridge-Field (ISMIR, 2004) Search Effectiveness http://ismir2004.ismir.net/proceedings/p051-page-266-paper135.pdf Uses 100,000 musical incipits Also: Sapp, Shanahan: Rhythmic search in 1m+ incipits CS 275A/Music 253 2019 Eleanor Selfridge-Field

Studies comparing analytical tools Claire Arthur MEI Proceedings (2015) Compares, Humdrum, MEI Johanna Devaney, Hugh Gauvin (Springer Verlag, 2016) Advocates extensions to Humdrum and MEI CS 275A/Music 253 2019 Eleanor Selfridge-Field

2019 Eleanor Selfridge-Field Neuromusicology Carol Krumhansl: Tonal, harmonic understanding Their physiological correlated Petr Janata: specific-key perception Neural correlates Petri Toiviainen Spatial-temporal music cognition CS 275A/Music 253 2019 Eleanor Selfridge-Field