This week, I personally worked on my portions of creating the ASL testing/training data, adjusting the instructional material (videos and text) to make sure it fits with how our model is reading hand data (i.e. making sure hands are angled so that all/most fingers are visible in frame), and locally examining the web app + ML models.
In regard to examining the web app, I have been brainstorming with Valeria on some of the suggestions that were given to us on our previous week meeting, where we are trying to decide the best way to store user statistics, include a random quiz mode for users to use with the ability for them to select which categories to be tested on, and format/display user profile information. As for the machine learning models, I have been locally working with them to see which is performing the best (currently the 1 finger model is) and to try to determine holes in how they have been trained (i.e. the sign for ‘d’ requires a certain tilt for it to be accurately detected). After identifying some of these signs, I have been working with Aishwarya to figure out solutions for theses issues in the models.
Our schedule is technically on schedule but is in danger of being behind, especially because my other two group members tested positive for Covid this past week. To account for this, we are pushing some tasks back a week on our schedule (such as integration) and doing our best to collaborate virtually.
In the next week, we plan to successfully execute an interim demo with most if not all of the static sign models working, along with a webapp that can teach users the ASL terms we have chosen after they make an account on the platform.