Technologies: Javascript, D3, Python, Linux
ABOUT:
ASL-LEX is a database of lexical and phonological properties of nearly 1,000 signs in American Sign Language. This project is a collaboration between the Laboratory for Language and Cognitive Neuroscience at San Diego State University and the Psycholinguistics and Linguistics Lab at Tufts University. ASL-LEX is a searchable database of subjective frequency ratings, iconicity ratings, lexical properties (e.g., initialized signs; lexical class), and six phonological features from which neighborhood densities have been calculated. ASL-LEX also provides, reference video clips, English translations and, for a subset of signs, alternative translations.
WHAT I DID:
During my internship at the Software Application & Innovation Lab, I worked with fellow software engineers and American Sign Language researchers to migrate the previous version ASL-LEX into the new version. The first version was being used in a third party application, and my team and I was tasked to develop a web application with additional features.
This was an extremely challenging project. I had to create a data pipeline with python to manage more than 2GB of American Sign Langauge data. It was quite difficult to clean and manage the massive dataset. I then developed python and shell scripts on a linux server in order to process all that information. It was taking 24-48 hours just to execute a script on my local machine. I then parsed that data and displayed it within a graph network visualization using Javascript D3 visualization library. Although, this was by far one of the most challenging projects I've worked on, I'm grateful to SAIL and the Hariri Institute for giving me a great opportunity and believing in me.