Python toolkit for articulatory phonetic analysis of image data: lingual ultrasound and video of facial landmarks. Facial landmark detection is carried out using dlib on images preprocessed with opencv3 and ndimage. (Ultrasound feature extraction TBA.) Dimensionality reduction is carried out using scikit-learn.
Files in the scripts directory also carry out forced alignment and acoustic analysis routines from various stages of writing my dissertation; these and the ultrasound analysis routines they coincide with will eventually be converted to functions in a sensible namespace.
The following dependencies, among others, are required for facial feature extraction using the functions and classes in imgphon/imgphon: opencv3, imutils, and dlib. The dependencies for dlib are especially large and complex. We have used the installation instructions for dlib on Unix-type systems at bit.ly/2HEhCQP with some success. The instructions provided at davisking/dlib may also help.
To configure upon downloading the package, simply navigate to the root directory of the repo and run python setup.py install.
A demonstration of lip shape extraction and dimensionality reduction can be found in lip-demo.ipynb. A demonstration of some tools for extracting and processing ultrasound video frames from the Telemed EchoBlaster's binary outputs can be found in echob-data-demo.ipynb. Use of these extracted features for analysis coming soon.
Coming soon