Which Aural Skills are Necessary for Composing, Performing and Understanding Electroacoustic Music, and to what Extent are they Teachable by Traditional Aural Training?
Why this work is in the frame
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Bibliographic record
Abstract
This paper reports a study that sought to discover the necessary aural skills for composing, performing, and understanding electroacoustic (EA) music and the extent of their teachability by traditional aural training according to an analysis of a mixed-method (qualitative/quantitative) questionnaire completed by a purposive sample of 15 experts in the field of electroacoustics. The participants evaluated a list of 50 potentially necessary aural skills, which were gathered from skills described in existing, but insufficiently applied, aural training systems and theoretical methods related to aural perception in EA, and provided additional skills they found necessary for EA. The survey revealed that the aural skills deemed the most necessary for EA by the participants were not regarded as sufficiently teachable by traditional aural training and the majority of the skills considered teachable by traditional aural training were not thought of as significantly necessary for the EA musician. Moreover, among the 50 skills listed in the questionnaire 56 per cent were deemed at least very necessary by the participants, with only 18 per cent of them viewed as sufficiently teachable by traditional aural training. The main implication of this study is a pressing need for further development, research, and experimental testing of aural training methods for EA.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it