  We introduce BlaBla, an open-source Python library for extracting linguistic
features with proven clinical relevance to neurological and psychiatric
diseases across many languages. BlaBla is a unifying framework for accelerating
and simplifying clinical linguistic research. The library is built on
state-of-the-art NLP frameworks and supports multithreaded/GPU-enabled feature
extraction via both native Python calls and a command line interface. We
describe BlaBla's architecture and clinical validation of its features across
12 diseases. We further demonstrate the application of BlaBla to a task
visualizing and classifying language disorders in three languages on real
clinical data from the AphasiaBank dataset. We make the codebase freely
available to researchers with the hope of providing a consistent,
well-validated foundation for the next generation of clinical linguistic
research.
