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Usability Ichiro Fujinaga McGill University 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) 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 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 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 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 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 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 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 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 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 agreedupon measures against agreed-upon collections of data, so that meaningful comparisons can be made between different research efforts. 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 • Lee, J., J. Downie, and S. Cunningham. 2005. Challenges in crosscultural/multilingual music information seeking. Proceedings of the International Conference on Music Information Retrieval. 1-7. Leong, T., F. Vetere, and S. Howard. 2006. Randomness as a resource for design. In Proceedings of the 6th ACM Conference on Designing interactive Systems, 132-9. • Randomwebsearch.com • randomwebsite.com/ • www.strangebanana.com/generator.aspx Other usability studies • Variations (Indiana Music Library) • Design guidelines and user-centered digital libraries (Theng et al.)