ZHAW/BA_TTS_Annotation_Plattform
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

feat: updated readme

Browse Source
This commit is contained in:
averel10
2026-06-02 09:11:45 +02:00
parent 8eb51dd406
commit cd6ea8ec99
1 changed files with 20 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

21
README.md
View File

@@ -104,4 +104,23 @@ After successful upgrade:
- The token becomes invalid
- Your account gains full admin privileges
- No new token is generated (admin now exists)
- Trying to upgrade another account will fail (token is spent)
- Trying to upgrade another account will fail (token is spent)
## Data Model
The application schema is defined with Drizzle ORM under `src/lib/model/`. Below are short descriptions of the available schema files and what they represent; see the files themselves for full structure.
- `auth-schema.ts` — user and authentication-related tables: `user` (accounts and admin flag), `session` (auth sessions), `account` (external OAuth/accounts), and `verification` (verification tokens).
- `dataset.ts` — `dataset` table: logical collections of audio items and dataset-level metadata.
- `dataset_entry.ts` — `dataset_entry` table: individual audio metadata rows belonging to a dataset (file path, speaker id, dialect labels, metrics, etc.).
- `experiment.ts` — `experiment` table: admin-configured annotation experiments referencing a dataset and experiment settings.
- `experiment_calibration.ts` — `experiment_calibration` table: ordered calibration items (audio + labels) used when `calibrationEnabled` is set on an experiment.
- `annotation.ts` — `annotation` table: annotator responses for dataset entries within experiments (rating, confidence, chosen dialect label); includes a uniqueness constraint to avoid duplicate annotations per user/item/experiment.
- `participant.ts` — `participant` table: links users to experiments and stores onboarding/calibration answers per participant.
When you change the model files in `src/lib/model/`, run the migration steps in "Modifying the Data Model" to generate and push migrations.
## Logical Steps: Creating and publishing an experiment
1. Create a new dataset containing all Samples. Can also be created by duplicating an already present dataset.
2. Create a new experiment using a dataset.
3. Publish the experiment.