• Introduction
• Introduction to the Internet (pdf) 
• Networks

• Research topics
• Research at DDMAL
• Other Databases

• Standards and Representations

Slide or HTML presentation I (10 min)

• Mael: Weimar Jazz Database
• Paul: MedleyDB and other multitrack datasets
• Marisa: DIAMM

• Classifiers (genre, instrument, mood, performer, composer, rhythm, beat tracking, etc.)

Slide or HTML presentation I

• Eto: Piano performance datasets (MAESTRO, ASAP, SUPRA-AW, etc.)
• Brady: Lakh MIDI Dataset
• Yifan: MusicBrainz
• Margaret:  Choral Public Domain Library
• Corinne: Aria Database
• Yu: GuitarSet
• Miranda: IMSLP/Petrucci Music Library

• Recognition and Analysis
• MIREX

Slide presentation II (15 min)

• Margaret: Lossless file formats (FLAC, MPEG-4, etc.)
• Paul: Game Boy Sound
• Brady: AIFF
• Mael: MIDI
• Corinne: MPEG-1 (MP3)

• Transcriptions and Annotations

Slide-based presentation II 

• Eto: Psychoacoustic model for audio compression
• Yifan: MEI
• Marisa: WAV/WMA
• Miranda: MusicXML
• Yu: kern / Humdrum

• Recommendations
• Playlists
• Web services

Slide-based presentation III (15 min)

• Mael: Gussian Mixture Models
• Marisa: Feature exraction (symbolic)
• Eto: Decision-tree algorithms

• Study Week: No class

• Similarity

Slide-based presentation III 

• Paul: Random Forest
• Margaret: Dynamic programming
• Corinne: Artifical Neural Networks
• Yifan: Convolutional Neural Networks
• Yu: Recurrent Neural Networks
• Brady: LSTM
• Miranda: HMM

• Query

Slide-based presentation IV (15 min)

• Eto: Automatic chord recognition
• Yifan: Chinese opera genre classification
• Mael: jSymbolic

03/21

• Indexing
• Watermarks
• Usability
• Systems issues

Slide-based presentation IV 

• Paul: jAudio
• Marisa: Taxonomy and music genre classification
• Brady: Key detection
• Corinne: Timbre recognition
• Miranda: Masataka Goto’s works

03/28

• Networked Environment for Music Analysis (NEMA)
• NEMA-DIY demo video
• Performance RENdering CONtest for computer systems (RENCON)

Slide-based presentation IV 

• Yu: Multi-f0 estimation
• Margaret: Beat and tempo tracking using audio

Slide-based presentation V (10–15 min)

Submit a draft of the final project proposal (1–2 pages) plus a partial bibliography

• Miranda: Polyphonic automatic music transcription
• Mael: Form recognition

• Web applications
• Ajax (e.g., Gmail, Google Maps, Google Suggest) Live example
• JavaFX
• HMTL5 / Javascript (a demo)
• SOA (service-oriented architecture)
  • loosely coupled and interoperable services
  • web services
  • mashups
• Web 2.0 (map)
  • Collaboration
  • Tagging
  • Folksonomy
  • Crowdsourcing: SurveyMonkey, MTurk, Zooniverse
  • IIIF

Slide-based presentation V 

• Brady: Bibliometric analysis of music technology disciplines
• Eto: Web-based music notation system
• Yifan: Guqin tablature and general tablature studies in MIR
• Marisa: Music search system design
• Paul: Playlist generation
• Corinne: Vocal analysis

• Intellectual property issues
• Copyright Quiz
• Michael Geist on Canada’s music copyright laws
• Supreme Court of Canada decisions on copyright (2012/07)
• Revised CAUT Guidelines for the Use of Copyrighted Material (2013/02)
• Michael Moore on sharing
• RIAA on piracy
• Steve Jobs on DRM
• P2P users spend 50% more on music than non-P2P users
• Creative Commons guide
• Socio-cultural aspects
• Course evaluation (deadline: 05/01)
  • Information
    • Video 1 (Why?) (2 min.)
  • Provide constructive feedback
    • Video 2 (How?) (3 min.)
  • Granted permission to disseminate your numerical course evaluation results (with minimum of five responses).

Note: We will meet online for this last class.

Slide-based presentation V 

• Margaret: Melody extraction

Final project presentations (8 min)

• Yu: Guitar tuning estimation
• Yifan: GuqinMEI: S module for encoding character-based Guqin tablature
• Eto: Web-based Guqin tablature editor
• Mael: Statistical features of model-sequences in Beethoven piano sonata developments
• Miranda: A review of polyphonic automatic music transcription
• Margaret: Differences between rubato in solo and accompaniment voices in 18th and 19th century music
• Brady: Bibliometric music technology analysis web application
• Marisa: The evolution of music databases
• Corinne: Genre classification of rap and chant based on vocals
• Paul: GBS-MDB: The Game Boy music database

Submit the final project proposal (1–2 pages) with a full bibliography

Assignments

Assignment #1 (Due 01/24) 4%

Subscribe to the ISMIR Google Community Announcements: https://groups.google.com/a/ismir.net/forum/#!forum/community

HTML- or slide-based presentation of existing music databases. Describe the content, history, and uses of the database, highlighting any research conducted with it. (10 min). Submit the HTMl pages or slides as a PDF file:

• Themefinder
• Meldex
• Cantus & Cantus Index
• IMSLP / Petrucci Music Library
• Choral Public Domain Library
• Museopen
• Aria
• Corpus Mensurabilis Musicae Electronicum
• MIDI databases (e.g., kunstderfuge.com)
• Million Song Dataset, Lakh MIDI Dataset, Slakh Dataset
• McGill Billboard Dataset
• Multitrack Datasets: MedleyDB, Open Multitrack Testbed
• Online music stores (e.g., Grooveshark, iTunes, Rhapsody, Spotify, Pandora, Rdio, etc.) (a review)
• More...

• Slide-based presentation of audio file formats: AIFF, WAV/WMA, Opus (Ogg Vorbis), Lossless formats (FLAC), etc.; MPEG formats: MPEG1 (MP3), MPEG4 (AAC), MPEG7, & MPEG21; symbolic fille formats: MEI, MusicXML, MIDI, etc., or audio compression techniques. Submit the slids as a PDF file.
• Annotated bibliography (short summary and evaluation) as a PDF file (use links, if avialable) (Chicago style, Documentation II: Author-Date References, 17th edition)

• Slide-based presentation of review of topics related to classifiers, e.g.: Feature extraction (audio or symbolic), Neural Networks (shallow, deep, CNN, RNN, LSTM, etc.), Support Vector Machines, Decision Tree (ID3), Random Forest, Gradient Boosting, Gaussian Mixture Models, Hidden Markov Models, AdaBoost, and Dynamic Programming; include music information retrieval applications. Submit the slids as a PDF file.
• Written summary (2–3 pages, single spaced, single or double columns, 1" margins) plus an annotated bibliography (Chicago style, Documentation II: Author-Date References,17th edition)

• Slide-based presentation on topics of transcription, recognition, annotation, and classification. It may include general review of transcription systems (monophonic, polyphonic, separation): Beat-box transcription, singing transcription, beat/tempo tracking using audio, beat/tempo tracking using MIDI, blackboard polyphonic transcription, Goto's works, historical overviews, real-time pitch tracking, piano music transcription, timbre recognition, genre classification, review of a component of jMIR, etc. Submit the slids as a PDF file.
• Written summary (2–3 pages) with an extensive bibliography (Chicago style, Documentation II: Author-Date References, 17th edition), which should include practically all significant papers on the subject. You do not need to annotated them but should reference each one of them in the summary paper.

Slide-based presentation on review of topics related to similarity, query systems, recommendation / playlist systems, or exploratory research on topics related to your final project. Submit the slides as a PDF file.

• Written summary (2–3 pages) plus an extensive bibliography (Chicago style, Documentation II: Author-Date References: 17th edition)

Assignment #6 (Due 03/28) 5%

• A draft of the final project proposal (1–2 pages), including a tentative title, subgoals, plus a partial bibliography (Chicago style, Documentation II: Author-Date References, 17th edition)

Assignment #7 (Due 04/11) 5%

• Final project presentation describing what you intend to do (5–8 min). Submit the slids as a PDF file.
• Final project proposal (1–2 pages) with the title and a full bibliography (Chicago style, Documentation II: Author-Date References, 17th edition)

• Software project with description (2–3 pages) (Repository on Github)

or

• Research paper (5–10 pages) (ISMIR style)

Improving writing skills for McGill graduate students: Graphos