Alter Ego: A Generative Music Creation System
Bibliographic record
Abstract
AlterEgo is a generative music creation system based on Franciscco L6pez's "Sonic Alter Ego". This system attempts to learn the preferences of the user. The application is currently under development, and a first prototype is ready to use and explore. The goal is that the system would be trained to play in a manner that reflects the preference of the composer and eventually sound very similar to its 'teacher's' composing style. To achieve this, a combination of Genetic Algorithms and Markov Chains has been implemented. The training of the application is done through simple interaction by rating the material, which has been proposed by the system. The system was initially written by commission from sound artist Francisco L6pez [1] for his project "Sonic Alter Ego", which is one of the winners of the VIDA 10.0 awards for Art and Artificial life by Fundaci6n Telef6nica (Spain, 2007). \n \nProceedings of the International Computer Music Conference (ICMC 2009), Montreal, Canada
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".