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Usability. Fujinaga 2003. Uitdenbogerd, A., and R. Schyndel. 2002. A review of factors affecting music recommender success. International Symposium on Music Information Retrieval. 204-8. Design criteria for music recommender systems Survey of research into musical taste

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Usability l.jpg

Usability

Fujinaga 2003


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Uitdenbogerd, A., and R. Schyndel. 2002. A review of factors affecting music recommender success. International Symposium on Music Information Retrieval. 204-8.

  • Design criteria for music recommender systems

  • Survey of research into musical taste

  • Review of music recommenders

    • Provide personalized content to users

      • Messages

      • List of stories

      • Artwork

    • Collaborative filtering (collect users’ opinions, ranking)

    • Content-based filtering

  • Limitations:

    • Inadequate raw data (editorial information)

    • Lack of quality control (user preference)

    • Lack of user preferences for new recordings

      • Content-based analysis needed for new recordings

    • Presentation (mostly simple lists)


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Uitdenbogerd, A., and R. Schyndel. 2002. A review of factors affecting music recommender success. International Symposium on Music Information Retrieval. 204-8.

  • Goals

    • Simple to use with minimum of input

    • More effort in providing input lead to better recommendations

    • Choice of music based on preferences, style, or mood

  • Use existing research into factors affecting musical taste

    • Social psychology

    • Demographics for marketing


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Uitdenbogerd, A., and R. Schyndel. 2002. A review of factors affecting music recommender success. International Symposium on Music Information Retrieval. 204-8.

  • Existing research

    • Stable extraverts: solid predictable music

    • Stable introverts: classical and baroque styles

    • Unstable extraverts: romantic music expressing overt emotions

    • Unstable introverts: mystical and impressionistic romantic works

    • Aggressive: heavy metal or hard rock

    • Japanese adolescents: classical or jazz

    • Critical age: mean 23.5 years old

    • Occupation

      • Dressmakers: moderately slow

      • Typist: fast tempo

    • Socio-economic background

      • Upper class women: classical

      • Working class men: hillbilly (Indiana)

    • Consistency in ranking of classical and popular music

    • Enjoyment correlates to labeling (“romantic”, “Nazi”, none) or known composer’s name


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Uitdenbogerd, A., and R. Schyndel. 2002. A review of factors affecting music recommender success. International Symposium on Music Information Retrieval. 204-8.

  • Factors affecting music preference

    • Age

    • Origin

    • Occupation

    • Socio-economic background

    • Personality

    • Gender

    • Musical education

    • Familiarity with the music or style

    • Complexity of music

    • Lyrics


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Uitdenbogerd, A., and R. Schyndel. 2002. A review of factors affecting music recommender success. International Symposium on Music Information Retrieval. 204-8.

  • Genres / styles

    • AllMusicGuide.com: 531

    • Amazon,com: 719

    • MP3.com 430

  • Moods

    • 8 clusters with 67 moods (Hevner)

    • 10 clusters with 52 moods (Farnsworth 1958)

    • Features: tempo, tonality, distinctiveness of rhythm, pitch height


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Uitdenbogerd, A., and R. Schyndel. 2002. A review of factors affecting music recommender success. International Symposium on Music Information Retrieval. 204-8.

Techniques for music recommenders

  • Collaborative filtering

    • Feedback from users: ratings, annotations, time spent

  • Content-based filtering

    • Problem of extracting musical semantics from raw signal

    • Low-level features; notes, timbre, rhythm

    • High-level features: adjectives

    • Transcription, instrument identification, genre classifier

    • Similarity measure from user supplied example (Welsh et al.)

      • 1248 features, 10-15 second samples, k-NN


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Kim, J.-Y., and N. Belkin. 2002. Categories of music description and search terms and phrases used by non-music experts. International Symposium on Music Information Retrieval. 209-14.

  • Information needs (music as information)

    • Information-seeking towards the satisfaction of user

    • Why does the user seek information?

    • What purpose does the user believe it will serve?

    • What use does it serve when found?

  • Three basic “human needs”

    • Physiological (food, water, shelter)

    • Affective (emotional needs, e.g.: attainment, domination)

    • Cognitive (need to plan, need to learn skills)

  • Music IR has concentrated on cognitive needs

    • Not enough user need studies

    • Ignored affective needs

    • Ignored musical information needs


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Kim, J.-Y., and N. Belkin. 2002. Categories of music description and search terms and phrases used by non-music experts. International Symposium on Music Information Retrieval. 209-14.

  • Purpose: To relate descriptions of affect to specific musical works

    • “means” for listeners to express their information “needs”

  • Seven classical music: 22 subjects

    • 11 s.: Words to describe the music

    • 11 s.: Words used to search for the music

  • Words used grouped into seven categories

    • Mostly emotions and occasions or filmed events

  • Subjects had no formal musical training

    • Used non-formal music terms

    • Terms not found in music query systems


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Futrelle, J., and J. Stephen Downie. 2002. Interdisciplinary communities and research issues in music information retrieval. International Symposium on Music Information Retrieval. 215-21.

  • Two main problems in MIR research

    • No evaluation method

    • Lack of user-need studies

  • Overemphasis on research in QBH systems is unsupportable given their doubtful usefulness

  • Research into recommender systems common in other domain is inexplicably rare

  • Lack of user interface research

  • Undue emphasis on Western music


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Futrelle, J., and J. Stephen Downie. 2002. Interdisciplinary communities and research issues in music information retrieval. International Symposium on Music Information Retrieval. 215-21.

First Principles of MIR:

  • MIR systems are developed to serve the needs of particular user communities.

  • MIR techniques are evaluated according to how well they meet the needs of user communities.

  • MIR techniques are evaluated according to agreed-upon measures against agreed-upon collections of data, so that meaningful comparisons can be made between different research efforts.


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Blandford, A., and H. Stelmaszewska. 2002. Usability of musical digital libraries: A multimodal analysis. International Symposium on Music Information Retrieval. 231-7.

Evaluation of four web-accessible music libraries.

  • www.nzdl.org music

  • www.nzdl.org video

  • ABC Tunefinder

  • Folk Music Collection

  • Aimed at different user community (different levels of technological and musical knowledge)

  • Too many file format choice for novices


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Other usability studies musical digital libraries: A multimodal analysis.

  • Variations (Indiana Music Library)

  • Design guidelines and user-centered digital libraries (Theng et al.)