The SIMSSA Project: Search as access to digital music libraries

Slides:



Advertisements
Similar presentations
ISVR Seminar 16 March 2010 MusicSpace: Orchestrating Musicological Metadata
Advertisements

Using Pivots to Explore Heterogeneous Collections A Case Study in Musicology Daniel Alexander Smith 8 December 2009.
Pseudo-Relevance Feedback For Multimedia Retrieval By Rong Yan, Alexander G. and Rong Jin Mwangi S. Kariuki
Providing collections, tools and services for digital humanities A national library perspective Clément Oury Head of Digital Legal Deposit Bibliothèque.
Computer Application and Resources in Music Scholarship Ichiro Fujinaga McGill University.
1/41 OCVE 2004 Fujinaga Levy Sheet Music Project and Optical Music Recognition introducing Gamut Ichiro Fujinaga McGill University OCVE Workshop (May 2004)
ELPUB 2006 June Bansko Bulgaria1 Automated Building of OAI Compliant Repository from Legacy Collection Kurt Maly Department of Computer.
A multimodal dialogue-driven interface for accessing the content of recorded meetings Agnes Lisowska ISSCO/TIM/ETI University of Geneva IM2.MDM Work done.
Document Image Analysis CSE 717 An Introduction. Document Image Analysis  DIA is the theory and practice of recovering the symbol structures of digital.
Computer Application and Resources in Music Scholarship the Present and the Future Susan Forscher Weiss Johns Hopkins University Ichiro Fujinaga McGill.
Transforming XML Into Music Notation Baron Schwartz, Computer Science Perry Roland, Digital Library Worthy Martin, Computer Science.
DigiMuse Digitalizing and Vocalizing Sheet Music for Mobile Devices running on Android OS by GOBİT.
Optical Music Recognition Ichiro Fujinaga McGill University 2003.
DIGITIZATION OF RARE LIBRARY MATERIALS Metadata Format Access to Digital Documents © Adolf Knoll, National Library of the Czech Republic.
JSymbolic and ELVIS Cory McKay Marianopolis College Montreal, Canada.
Million Book Project (MBP) Gloriana St. Clair Johns Hopkins University February 5, 2003.
European Metadata Initiatives: The METAe Metadata Engine Simon Tanner Higher Education Digitisation Service
Crowdsourcing Game Development for Collecting Benchmark Data of Facial Expression Recognition Systems Department of Information and Learning Technology.
OCLC Online Computer Library Center CONTENTdm ® Digital Collection Management Software Ron Gardner, OCLC Digital Services Consultant ICOLC Meeting April.
Contactforum: Digitale bibliotheken voor muziek. 3/6/2005 Real music libraries in the virtual future: for an integrated view of music and music information.
MusicXML David Sears MUMT September, 2009.
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.
Audio Fingerprinting MUMT 611 Ichiro Fujinaga McGill University.
ENOMA - European Network of Online Musical Archives ENOMA Workshop – The Grieg Academy, UiB 26 May 2006 Leif Arne Rønningen and Lars Erik Løvhaug NTNU.
PROJECT PROPOSAL DIGITAL IMAGE PROCESSING TITLE:- Automatic Machine Written Document Reader Project Partners:- Manohar Kuse(Y08UC073) Sunil Prasad Jaiswal(Y08UC124)
Symbolic Musical Analysis CS 275B/Music 254. Practicalities CS 275B2013 Eleanor Selfridge-Field2.
The SpokenWeb Project at Concordia University Annie Murray Digital & Special Collections Librarian Concordia University | Montréal.
From Manuscript to Printing Press to Computer Chip Studying Early Music in Digital Format Susan Forscher Weiss Johns Hopkins University Ichiro Fujinaga.
Gamera Optical Music Recognition in a New Shell Michael Droettboom, Karl MacMillan Sheridan Libraries Johns Hopkins University Ichiro Fujinaga McGill University.
Regional Workshop on the 2010 World Programme on Population and Housing Censuses: International standards, contemporary technologies for census mapping.
EXAMPLES OF DIGITAL ARCHIVES AND LIBRARIES Advanced Techniques in Processing Images Advanced Techniques in Processing Images Chapter 6. Slide 57.
Using Musical Information: Query, Analysis, and Style Simulation Mus 254/CS 275B/SSP 253b Stanford University Spring Quarter.
Ask a Librarian: The Role of Librarians in the Music Information Retrieval Community Jenn Riley, Indiana University Constance A. Mayer, University of Maryland.
NATURAL LANGUAGE PROCESSING Zachary McNellis. Overview  Background  Areas of NLP  How it works?  Future of NLP  References.
Soon Joo Hyun Database Systems Research and Development Lab. US-KOREA Joint Workshop on Digital Library t Introduction ICU Information and Communication.
MPEG-7 Audio Overview Ichiro Fujinaga MUMT 611 McGill University.
IIIF Ghent Report Randy Stern Chip Goines Harvard University IT Library Technology Services Bill Stoneman Houghton Library January 11, 2016.
Digitization of the Lester S. Levy Collection of Sheet Music Ichiro Fujinaga McGill University with Michael Droettboom, Karl MacMillan, G. Sayeed Choudhury,
1 Quebec Digital Infrastructure The Year in Review Guy Teasdale ACCESS 2006 Ottawa, October
1 / 22 jSymbolic Jordan Smith – MUMT 611 – 6 March 2008.
Digital OU September 15, Partners The Andrew W. Mellon Foundation Society for Classical Studies Medieval Academy of America Renaissance.
BASS TRACK SELECTION IN MIDI FILES AND MULTIMODAL IMPLICATIONS TO MELODY gPRAI Pattern Recognition and Artificial Intelligence Group Computer Music Laboratory.
© NCSR, Frascati, July 18-19, 2002 CROSSMARC big picture Domain-specific Web sites Domain-specific Spidering Domain Ontology XHTML pages WEB Focused Crawling.
A shallow description framework for musical style recognition Pedro J. Ponce de León, Carlos Pérez-Sancho and José Manuel Iñesta Departamento de Lenguajes.
Document Analysis Group
Michael Fingerhut Ircam, Paris (France)
for Musical Applications Using XML
Filigranes pour tous Watermarks For All
The LEFIS experiences and perspectives
Graduation Project Kick-off presentation - SET
Gamera A Toolkit for Structured Document Recognition including Music
“Which Line Is it Anyway”:
Cheng-Ming Huang, Wen-Hung Liao Department of Computer Science
Automatic Scoring-up of Mensural Parts
Optical Data Capture: Optical Character Recognition (OCR)
Unit# 6: ICT Applications
Metadata to fit your needs... How much is too much?
Optical Music Recognition
SAKAI February 2005.
IIIF AV Player Andrew Kam.
The SIMSSA DB Data Model
Guatemalan Manuscript Digitization Project
Text Mining & Natural Language Processing
Symbolic Musical Analysis
Interactive media.
How Digital Humanities adds to PhD Projects
New Platform to Support Digital Humanities in the Czech Republic
Automatic Handwriting Generation
Presentation transcript:

The SIMSSA Project: Search as access to digital music libraries Emily Hopkins SIMSSA Project Manager, McGill University Workshop on SIMSSA XV, IAML, Leipzig, 28 July 2018

SSHRC Partnership Grant (2014-2021) PI: Ichiro Fujinaga (McGill University) Partners include the British Library, Bodleian Libraries at Oxford, Bibliothèque Nationale de France, Bavarian State Library, New York Philharmonic Archives, Alexander Street Press, RILM, and RISM Switzerland among others PARTNER LIST -- Include all partners who will be at IAML!

How it works: Library digitizes scores Optical Music Recognition Symbolic Encoding with MEI Search and Analysis

How do we access the scores? How can we teach computers to read musical scores? How will music search and analysis work?

How do we access the scores?

International Image Interoperability Framework

MusicLibs.net Music libs Front page randomly serves up previews of scores in our database

How can we teach computers to read musical scores?

Optical Character Recognition Makes images of text machine-readable XML

Optical Music Recognition Makes images of sheet music machine-readable MIDI, MusicXML, MEI

Music Encoding Initiative (MEI) <music>     <body>         <mdiv>             <score>                 <scoreDef meter.count="2" meter.unit="4" key.sig="3s">                     <staffGrp symbol="line">                         <staffDef n="1" label="Singstimme." lines="5" clef.shape="G" clef.line="2"/>                         <staffGrp symbol="brace" label="Pianoforte.">                             <staffDef n="2" lines="5" clef.shape="G" clef.line="2"/>                             <staffDef n="3" lines="5" clef.shape="F" clef.line="4"/>                         </staffGrp>                     </staffGrp>                 </scoreDef>             </score>         </mdiv>     </body> </music> Example borrowed from the MEI tutorial at music-encoding.org; music is Robert Schumann’s Der Abendstern.

Commercial OMR

Salzinnes Antiphonal CDN Hsmu M2149.L4 http://cantus.simssa.ca Whatever ground truth we give it!

Pixel.js: Making ground truth data

Pixelwise Classification Calvo-Zaragoza, Jorge. “Pixelwise classification for music document analysis.” Presented at the Workshop on SIMSSA XII, August 7, 2017.

Interactive Classifier: Identifying glyphs & training our OMR

Neon.js: Correcting OMR output

Scoring-up Tool Slide courtesy of Thomae Elias, Martha Eladia, Julie Cumming, and Ichiro Fujinaga. “Automatic Scoring up of Music in Mensural Notation.” Presented at the 46th Medieval and Renaissance Music Conference, Maynooth, Ireland, July 2018.

Encoding rules for context-dependent mensural notation Relate to Measuring Polyphony Slide courtesy of Thomae Elias, Martha Eladia, Julie Cumming, and Ichiro Fujinaga. “Automatic Scoring up of Music in Mensural Notation.” Presented at the 46th Medieval and Renaissance Music Conference, Maynooth, Ireland, July 2018.

Crowdsourced OMR Correction Making tools more user-friendly Collaboration with Partner organizations and user communities

How will music search and analysis work?

Melodic Search Garfinkle, David & Peter Schubert. “Computer-Assisted Corpus Analysis Finds a Signature Progression in Willaert and Palestrina.” Presented at the 46th Medieval and Renaissance Music Conference, Maynooth, Ireland, July 2018.

https://patternfinder.elvisproject.ca/

Corpus Studies Schubert, Peter, and Julie Cumming. “Another Lesson from Lassus: Using Computers to Analyse Counterpoint.” Early Music 43, no. 4 (November 2015): 577–86.

Desmond, Karen, Emily Hopkins, and Sam Howes Desmond, Karen, Emily Hopkins, and Sam Howes. “Measuring Polyphony: Analysing Stylistic Change in the French Motet Repertory, C1300-1350.” Presented at the Workshop on SIMSSA VIII, McGill University, Montreal, QC, May 21, 2016. Comparing downbeats (only) to offbeats (only)

Percentage of perfect sonorities for all pieces

http://measuringpolyphony.org/

Arthur, Claire, Julie Cumming, and Peter Schubert Arthur, Claire, Julie Cumming, and Peter Schubert. “Computer-Assisted Modal Identification.” Presented at the 46th Medieval and Renaissance Music Conference, Maynooth, Ireland, July 2018.

Machine learning and composer identification McKay, Cory, Tristano Tenaglia, Julie Cumming, and Ichiro Fujinaga. “Using Statistical Feature Extraction to Distinguish the Styles of Different Composers.” Presented at the Medieval and Renaissance Music Conference, Prague, Czech Republic, July 4, 2017.

Thank you! https://simssa.ca/ emily.hopkins@mcgill.ca @simssaproject @e_a_hopkins