The most significant risks that could jeopardize the success of our project currently are the model accuracies. Over the past week, we have been looking at accuracy tradeoffs and started conducting user tests, and with the dynamic models, we can see that when users sign them quickly, our model is not able to accurately detect the dynamic signs. To fix this, we are considering making training data of doing the signs faster so that the model can be trained on faster iterations of each sign. As a contingency plan, we will just tell the user to sign slightly slower or just keep the models as they are since we are nearing the end of the semester.
There haven’t been any changes to our system design. As for our schedule, we are going to extend our user testing weeks all the way up to the demo since we were not able to get enough users to sign up over this past week. Additionally, we plan to collect survey results at the live demo to get more user feedback to add to the final report. Also, because we have the webapp and ML models fully integrated, we are shortening the integration task on our schedule by two weeks.