Data Code

KRAJJAT

Krajjat has been developed as a Python package for processing motion capture data and finding relationships between the kinematics of the tracked movements and the acoustic components of speech.

The toolbox allows to:

• Pre-process the motion capture sequences, via functions for de-jittering, re-referencing, trimming, resampling, and interpolating missing data.
• Get acoustic components of the speech, such as the envelope, the intensity, the pitch, or one of the formants.
• Convert the sequences and save them in different formats (.json, .xlsx, .txt, .csv, .tsv or .mat).
• Display the sequences, compare them side-by-side or overlayed, and save them as video files.
• Plot the movement or acoustic variables, either for a single joint or for all of them.
• Perform statistical analyses on the relationship between motion capture sequences and speech: power spectrum, correlation, coherence, mutual information, PCA and ICA.

The package can be installed using the command pip install krajjat.

Documentation:
https://krajjat.readthedocs.io/en/latest/

Repository:
https://github.com/RomainPastureau/Krajjat

PyPI page:
https://pypi.org/project/krajjat/

FIND_DELAY

find_delay is a Python package that tries to find the delay where a time series appear in another via cross-correlation. This package was created to find when an excerpt starts in a larger audio file, but can virtually work with any two time series. In MEG experiments it has been used to find the delay of the audio onset and to correlate eye-tracking data with EOG channels.

The package can be installed using the command pip install find-delay.

Documentation:
https://find-delay.readthedocs.io/en/latest/

Repository:
https://github.com/RomainPastureau/find_delay

PyPI page:
https://pypi.org/project/find-delay/