Recent Changes

Saturday, November 9

  1. page Program suggestions edited ... Journal of the International Society for Music Information Retrieval (JISMIR). Selected papers…
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    Journal of the International Society for Music Information Retrieval (JISMIR). Selected papers of the conference (based on votes by the program committee, probably) get the chance to be extended and published at this Journal.
    If you have any more ideas, please feel free to add them here. If you are really interested in any of these topics, please also feel free to create a new section for it and extend it. Mohamed Sordo
    About the JISMIR, it's regular to select papers of the conference. Is it possible to combine the results of MIREX contest and submissions of ISMIR (not just conference paper), which could have some late-breaking of their research, but not ready on the time frame of ISMIR submission and review (it almost has 6 months different from submission to conference holding.)? The factors of consideration could be not published with certain period from beginning of the research topic and have good result on MIREX with first priority. Frank Wu
    8. Realizing Semantic Web Technologies in Music Digital Libraries
    A digital library is defined as: afocused collection of digital objects—including text, audio and video—along with methods for access and retrieval, and for selection, organisation, and maintenance. Recent work at Illinois, McGill Oxford, and Waikato Universities has shown how semantic web technologies can be integrated into this definition, using music digital libraries as a motivating example. The end result goes beyond traditional expectations as to what this type of digital resource can provide. Two specific realizations of this work are: i) the SALAMI Linked Data Resource (including a Sparql endpoint) providing a gateway to over 2.1 million music segmentation files; and ii) Unchained Melody -- a sequence of musical digital libraries that demonstrates how semantic web technologies can change the services provided by a digital music library.
    (view changes)

Friday, November 8

  1. page Program suggestions edited ... - Labels evaluation: Pair-wise clustering vs entropy values (vs random? vs ...?). Which one is…
    ...
    - Labels evaluation: Pair-wise clustering vs entropy values (vs random? vs ...?). Which one is more reliable? What are the pros/cons of each?
    - Deep Learning: Can we learn better structural features automatically? Most of the publications on music segmentation either use MFCC or Chromas (and when they combine them, it's usually simply by stacking one on top of the other). Could we use deep learning to learn a representation that captures both timbre and harmony (and maybe rhythm and... melody lines?) in an optimal way for music segmentation?
    - ...Perception and functional structure: is there more room to use perception and cognition findings in segmentation tasks?
    - Vice versa: can our annotated data be used to address questions in the perception of boundaries and structural function. What data would be needed to answer more of them? (@jvanbalen)

    7. Here's an additional list of topics or ideas that I'd like to see discussed at the D&LB session this year.
    Linked Data in MIR, ontologies.
    (view changes)
  2. page Program suggestions edited ... A review of state-of-the-art in MIR applied to music education. Reflection on shortcomings of…
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    A review of state-of-the-art in MIR applied to music education.
    Reflection on shortcomings of previous projects in this area.
    ...
    MIR developments (for example, deep learning, culture-dependent MIR, computational creativity) opened up new possibilities?
    Differences in music teaching approaches influenced by culture/region.

    Relating more general applications of AI, data-mining, signal processing, cognitive science, psychology and software engineering to education (see additional links below).
    The desired extent of the involvement of MIR in music education.
    (view changes)
  3. page Program suggestions edited ... I would like to propose a discussion on how various MIR techniques have been/can be applied to…
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    I would like to propose a discussion on how various MIR techniques have been/can be applied to music education. Sometime ago I came across the Songs2See project from Fraunhoffer IDMT at the Music Tech Fest held in London this year. It was very interesting to see how using MIR, music education can be tailored to individual students' needs and interests, with the possibility of making the learning experience engaging. Another project which focuses on making music education more accessible, while at the same time making it easier for teachers to attend to many students is PRAISE. A related initiative in this regard which deals more generally with education is the recent NIPS workshop on Personalizing Education with Machine Learning.
    My aim in proposing this discussion is to learn more about how MIR can be applied to shape music curricula, to make music education more accessible to everyone, particularly those that do not have easy access to music schools, or cannot afford to enroll in full-time courses at universities due to limited availability of time or funds. I would like to hear the opinions of those that have experience in teaching music, or have studied music at university about different ways in which MIR can be incorporated into music education, and the possible benefits of this. I welcome any comments/links related to this subject that will help the discussion.
    A few simple ideas:
    Score-following algorithms
    Tentative pathway for sight-reading practice.
    Source-separation for jamming/playing along with accompaniment.
    Generative AI models for practice exercise creation.
    Music cognition studies
    discussion:
    A review of state-of-the-art in MIR applied
    to design feasible teaching/learning practicesmusic education.
    Reflection on shortcomings of previous projects in this area.
    How have recent MIR developments opened up new possibilities?
    Relating more general applications of AI, data-mining, signal processing, cognitive science, psychology
    and implementing effective intelligent tutoringsoftware engineering to education (see additional links below).
    The desired extent of the involvement of MIR in music education.
    Specific learning tasks (composition, improvisation, etc.) that can benefit from MIR
    systems.
    Youtube crawling for crowdsourced video learning resources.

    Some additional links:
    International Education Data-Mining Society
    (view changes)
  4. page Program suggestions edited ... I would like to propose a discussion on how various MIR techniques have been/can be applied to…
    ...
    I would like to propose a discussion on how various MIR techniques have been/can be applied to music education. Sometime ago I came across the Songs2See project from Fraunhoffer IDMT at the Music Tech Fest held in London this year. It was very interesting to see how using MIR, music education can be tailored to individual students' needs and interests, with the possibility of making the learning experience engaging. Another project which focuses on making music education more accessible, while at the same time making it easier for teachers to attend to many students is PRAISE. A related initiative in this regard which deals more generally with education is the recent NIPS workshop on Personalizing Education with Machine Learning.
    My aim in proposing this discussion is to learn more about how MIR can be applied to shape music curricula, to make music education more accessible to everyone, particularly those that do not have easy access to music schools, or cannot afford to enroll in full-time courses at universities due to limited availability of time or funds. I would like to hear the opinions of those that have experience in teaching music, or have studied music at university about different ways in which MIR can be incorporated into music education, and the possible benefits of this. I welcome any comments/links related to this subject that will help the discussion.
    A few simple ideas:
    Score-following algorithms for sight-reading practice.
    Source-separation for jamming/playing along with accompaniment.
    Generative AI models for practice exercise creation.
    Music cognition studies to design feasible teaching/learning practices and implementing effective intelligent tutoring systems.
    Youtube crawling for crowdsourced video learning resources.

    Some additional links:
    International Education Data-Mining Society
    ...
    - Labels evaluation: Pair-wise clustering vs entropy values (vs random? vs ...?). Which one is more reliable? What are the pros/cons of each?
    - Deep Learning: Can we learn better structural features automatically? Most of the publications on music segmentation either use MFCC or Chromas (and when they combine them, it's usually simply by stacking one on top of the other). Could we use deep learning to learn a representation that captures both timbre and harmony (and maybe rhythm and... melody lines?) in an optimal way for music segmentation?
    - Datasets: How many annotations per piece would be ideal? How can we add this information to our evaluation metrics?
    - ...
    7. Here's an additional list of topics or ideas that I'd like to see discussed at the D&LB session this year.
    (view changes)
  5. page Program suggestions edited ... - Labels evaluation: Pair-wise clustering vs entropy values (vs random? vs ...?). Which one is…
    ...
    - Labels evaluation: Pair-wise clustering vs entropy values (vs random? vs ...?). Which one is more reliable? What are the pros/cons of each?
    - Deep Learning: Can we learn better structural features automatically? Most of the publications on music segmentation either use MFCC or Chromas (and when they combine them, it's usually simply by stacking one on top of the other). Could we use deep learning to learn a representation that captures both timbre and harmony (and maybe rhythm and... melody lines?) in an optimal way for music segmentation?
    - Datasets: How many annotations per piece would be ideal? How can we add this information to our evaluation metrics?
    - ...
    7. Here's an additional list of topics or ideas that I'd like to see discussed at the D&LB session this year.
    (view changes)
  6. page Program suggestions edited ... [Srikanth Cherla] I would like to propose a discussion on how various MIR techniques have bee…
    ...
    [Srikanth Cherla]
    I would like to propose a discussion on how various MIR techniques have been/can be applied to music education. Sometime ago I came across the Songs2See project from Fraunhoffer IDMT at the Music Tech Fest held in London this year. It was very interesting to see how using MIR, music education can be tailored to individual students' needs and interests, with the possibility of making the learning experience engaging. Another project which focuses on making music education more accessible, while at the same time making it easier for teachers to attend to many students is PRAISE. A related initiative in this regard which deals more generally with education is the recent NIPS workshop on Personalizing Education with Machine Learning.
    ...
    to this mattersubject that will
    Some additional links:
    International Education Data-Mining Society
    (view changes)
  7. page Program suggestions edited ... [Srikanth Cherla] I would like to propose a discussion on how various MIR techniques have bee…
    ...
    [Srikanth Cherla]
    I would like to propose a discussion on how various MIR techniques have been/can be applied to music education. Sometime ago I came across the Songs2See project from Fraunhoffer IDMT at the Music Tech Fest held in London this year. It was very interesting to see how using MIR, music education can be tailored to individual students' needs and interests, with the possibility of making the learning experience engaging. Another project which focuses on making music education more accessible, while at the same time making it easier for teachers to attend to many students is PRAISE. A related initiative in this regard which deals more generally with education is the recent NIPS workshop on Personalizing Education with Machine Learning.
    ...
    and the pros and cons involved in doingpossible benefits of this. I
    Some additional links:
    International Education Data-Mining Society
    (view changes)
  8. page Program suggestions edited ... International Education Data-Mining Society i-Maestro ... Data Mining , Intelligent Tutor…
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    International Education Data-Mining Society
    i-Maestro
    ...
    Data Mining , Intelligent Tutoring Systems on Wikipedia.
    6. Music Segmentation: Perception, Evaluation and Inherent Challenges
    [Oriol Nieto, @urinieto]
    (view changes)
  9. page Program suggestions edited ... International Education Data-Mining Society i-Maestro ... Mining on Wikipedia Wikipedia.…
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    International Education Data-Mining Society
    i-Maestro
    ...
    Mining on WikipediaWikipedia.
    6. Music Segmentation: Perception, Evaluation and Inherent Challenges
    [Oriol Nieto, @urinieto]
    (view changes)

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