This is typically done (repeatedly!) in the process of importing your data into our format for the first time, but you should also do this whenever you make a change to the dataset.
Looks for errors and inconsistency in the metadata, or for missing audios. The validation will pass if formatting instructions are met (see format).
child-project validate /path/to/dataset --help
Example:
# validate the metadata and raw recordings
child-project validate /path/to/dataset
# validate the metadata only
child-project validate /path/to/dataset --ignore-recordings
# validate the metadata and the recordings of the 'standard' profile
# (in recordings/converted/standard)
child-project validate /path/to/dataset --profile standard
# validate the metadata and all annotations within /path/to/dataset/annotations
child-project validate /path/to/dataset --ignore-recordings --annotations /path/to/dataset/annotations/*
# validate the metadata and annotations from the 'textgrid' set
child-project validate /path/to/dataset --ignore-recordings --annotations /path/to/dataset/annotations/textgrid/*An overview of the contents of a dataset can be obtained with the child-project overview command.
child-project overview --help
Example:
$ child-project overview .
recordings:
lena: 288.00 hours, 0/18 files locally available
olympus: 49.57 hours, 0/3 files locally available
usb: 223.42 hours, 0/20 files locally available
annotations:
alice: 560.99 hours, 0/40 files locally available
alice_vtc: 560.99 hours, 0/40 files locally available
eaf/nk: 1.47 hours, 0/88 files locally available
lena: 272.00 hours, 0/17 files locally available
textgrid/mm: 8.75 hours, 0/525 files locally available
vtc: 560.99 hours, 40/40 files locally availableCompute recordings duration in ms and store in into a column named ‘duration’ in the metadata.
child-project compute-durations /path/to/dataset --help
Compute the correlation between two audio files and prints a divergence score. The divergence is computed over a given duration (default 5min) that can be changed with the --interval option. One segment of that duration is taken randomly, the difference in audio signal is calculated and averaged over the total duration. The result is printed as a divergence score. The closer the score is to 0, the more likely it is the 2 files are identical. We can consider that scores below 0.1 reflect a very high probability that the files are the same. At the other end of the spectrum, values higher than 1 almost certainly means they are different recordings. So a window exists in which we can't be sure and would need additional correlation computations or manual checks. Running the correlation multiple time is useful because files that are different have a high variability in score whereas similar files will have a much more consistent output.
Giving a higher --interval value may take more time to compute.
child-project compare-recordings /path/to/dataset --help