preparation:

1. copy cerevoice_eng/ and voice/ folders into preprocessing/
   • voice/ has to contain both voice and licence files
2. optional: copy bbdf and refdf files to preprocessing/data/

usage: run preprocessing/create_json.py with python 2.7 (--h for list of available arguments)

• specify location of bbdf and refdf files with --o , if files are not in preprocessing/data
• default output folder: preprocessing/data/output

preparation:

1. copy images/ , audio/ and json/ from Slurk static folder into evaluation/data/
2. copy corresponding log file(s) into evaluation/data/

usage: run evaluation/evaluate_logs.ipynb with Jupyter Notebook

preparation

1. create config.ini (copy from config.template.ini)
2. fill in AWS credentials, change urls if slurk is not hosted locally ('link_generator' and 'login' sections)
3. set 'value' to 'true' if used in production ('false' for sandbox)

publishing HITs

• execute publish_hits.py to publish HITs on AMT (specify number of HITs using the -n argument)
• all HIT IDs are registered in JSON files in the 'published' directory

deleting HITs

• execute delete_hits.py to delete all HITs found in the 'published' directory