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Gyorgy Fazekas, 2012-02-23 01:02 PM

These notes are based on our initial meeting on 24 January 2012. The aim was to collect some use cases and have an initial idea on what needs to be done to extend or revise the existing Audio Features Ontology.

Topics discussed

A rough list of topics discussed during the first meeting:

  • What are the main research use cases for an Audio Features Ontology (AF) ?
  • Are they served well by the existing AF ?
  • If not, what are the most important extensions we need to do?
  • Does the fundamental structure of the ontology need to be changed?
  • What is the relation of AF to existing software, including:
    • software like: Sonic Annotator, Sonic Visualiser, SAWA, AudioDB other tools...
    • and projects like: OMRAS2, EASAIER, SALAMI, new Semantic Media/Semantic Audio grants...
  • Personal Objectives: what are we going to do with a modified/re-engineered ontology?

Use cases:

Use cases discussed so far:

Thomas:

  • drive audio effects -> adaptive effect (controlling effects)
  • KM like use case: association of audio effects and audio features e.g. pitch shifter won’t change onsets
  • part of the AFX ontology
  • more audio features
  • technical classification of audio effects
Steve:
  • Finding structure, repeated sequences of features
  • Beat related stuff, BPM (tempo, major/minor is it an audio feature, not necessarilty)
  • Chords => Chord ontology
  • Melody and notes
George:
  • Improve SAWA
  • Facilitate the development of intelligent music production systems
  • Release large content based metadata repositories in RDF
  • Re-release the MSD in RDF (??)
  • Deploy a knowledge based environment for content-based audio analysis based on the concept of the Knowledge Machine that can combine multiple modalities
  • Research reproducibility using Ontologies as a model to exchange research data.

Open issues:

Some important questions to be decided on:

Domain boundaries and scope:

  • Are Musicological concepts outside the domain of an AF ?
  • How about Physical features:
    • Acoustic features,
    • Perceptual Features,
    • DSP type feature,
    • Musical Features (musically meaningful features related to acoustics)
  • The scope of the revised ontology may be:
    • Facilitate data-exchange for various purposes: (e.g. Linked Open Data, Research reproducibility, etc...)
    • Facilitate building intelligent/knowledge-based systems:
      • How expressive the Ontology should be?
      • What kind of reasoning services should be supported?

What are the strength and weaknesses of the existing ontology?

  • Does it serve us well?
  • For example, loudness is defined as a segment in AF, and it does not fit a perceptual attribute well.
  • What depth do we want ? (both in terms of scope and the level of detail in describing a feature extraction workflow)
  • How AF relates to the DSP workflows used in extracting them?

Fundamental structure of the existing AF Ontology:

The Audio Features Ontology currently provides a core model which distinguishes between audio features based on two attributes:

  1. Temporal characteristics
  2. Data density

The first dichotomy allows for describing features either instantaneous events (e.g. note onsets, tempo change), or features with a known time duration (notes, structural segments, harmonic segments, the extent of an STFT or Chromagram frame).

The second dichotomy addresses a representational issue, and allows for describing how a feature relates to the extent of an audio file:
  • whether it is scattered and irregularly occurs during the course of a track (i.e. sparse),
  • or occurs regularly and have a fixed duration (i.e. dense).
    Alternative conceptualisations and some examples are summarised below:


Fig 1. Conceptualisations of content-based features.

The main scope of the existing ontology is to provide a framework for communication and to describe the association of features and audio signals. It does not classify features, describe their interrelationships or their computation. It deals with data density, and temporal characteristics only and differentiates between dense signal-like features of various dimensionality, (chromagrams, detection functions) and sparse features that are scattered across the signal timeline. This core model is shown in the following diagram:


Fig. 2. Core model of the existing Audio Features Ontology

Existing resources :

Some work related to Steve's use cases, segmentation and Ontologies:

Ideas/resources for new Ontologies:

  • Steve has worked on Acoustics related ontology
  • create an Acoustics Ontology
  • describe Musicological concepts
  • describe concepts related to cognitive and perceptual issues

Currently missing features

  • MFCC-s
  • Rythmogram
  • RMS energy
  • combined features, e.g. weighted combinations or statistical averages over features

Development issues

  • chaining, combination, weighting
  • how you associate features with arbitrary data
  • summary feature types
  • SM (similarity matrix) are they part of the ontoogy?
  • how to describe salience, can you hear it, can you perceive, is there an agreement
  • how to describe weighting, confidence
  • mood, music psychology, cognition, emotion, (perception ?)
  • provenance => music provenance
  • deprecation and versioning

Long term objectives:

Some concrete tasks that can be done as the outcome of the collaboration:

  • A version of Sonic Annotator that produces output adhering the new ontology
  • Are we making people happier by doing so?
  • gradual transition period?
  • extend other software toolkits; e.g. a verison of Marsyas in C++
  • multitrack processing using Sonic Annotator (this feature might come along soon)

Some immediate tasks (TODO):

  • collect more resources
  • Verify the relationship between AF as is, and other feature/segmentation Ontologies
  • what other software uses it?
  • papers and literature review
  • relation to projects e.g. SIEMAC
  • collect features that we need
  • define scope (extend the diagram of the set of ontologies: )
  • collect specific application examples from existing processing chain / workflow

collect software/projects that use/produce audio features:

  • plugins, LADSPA, VAMP, Marsyas, CLAM, libextract, COMirva, MIRtoolbox, Supercollider, other frameworks