Proceedings of the second international ACM workshop on Music information retrieval with user-centered and multimodal strategies
Bibliographic record
Abstract
It is our great pleasure to welcome you to the 1st International ACM Workshop on Music Information Retrieval with User-Centered and Multimodal Strategies (MIRUM). MIRUM was proposed in order to gather experts from the Music and Multimedia Information Retrieval communities, as well as other neighboring fields, and aims to provide a high-profile platform for presenting current work on Music Information Retrieval, with strong focus on user-centered and multimodal approaches. Music content is multifaceted and exists in many different representations, including audio recordings, symbolic scores, folksonomy descriptions and accompanying video material. No single representation is capable of accounting for all of the music experience, which is strongly guided by affective and subjective context- and user-dependent factors. The existence of complementary representations and information sources in multiple modalities makes music multimedia content by definition. Furthermore, the subjective and affective aspects of music pose challenges that are faced and experienced in the broad Multimedia community. Thus, we believe it is appropriate to discuss these topics in a Multimedia context. The MIRUM 2011 Call for Papers attracted 22 international technical submissions. The program committee accepted 9 papers that cover a wide variety of topics, ranging from beat tracking techniques to affective analysis of music videos. In addition, the full-day program includes a keynote speech by Dr. Roeland Ordelman (Netherlands Institute for Sound and Vision & University of Twente, The Netherlands) on exploitation possibilities of audiovisual data in the networked information society, as well as a panel on bridging opportunities for the music and multimedia domains, featuring multiple experts from the music and multimedia communities. We hope that these proceedings will serve as a valuable reference for researchers in the fields of Music and Multimedia Information Retrieval, as well as neighboring fields.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".