myInterpreter

Company Challenges

Best Overall Hack Best Use of Google cloud Sponsor Prizes Best Random Hack Best Social Justice Hack Best sustainability Hack Best Healthcare App

Inspiration

Feeling like there is a need for the hard of hearing to also feel included and be able to freely communicate with others in the society, we developed this solution to tackle this problem so we could bridge the communication gap between them and the society

What it does

Transforms sign language into written text and sends it over to the receiver of the information in both speech and text for easier comprehension of information from the hearing impaired

How we built it

We used computer vision to track the hands and funneled data from different hand signs. We created a predictive analysis using a classifier model to distinguish this signs from one another. We used this created model to further identify hand signs similar to those of the trained data and predict their respective meanings

Challenges we ran into

The first challenge we ran into was figuring how to use openCV to recognize our hands The second challenge was finding biases within our data like mis identifying right from left hands or under fitting our model The third and biggest model we faced was trying to standardize the data properly to function efficiently. This took hours but we figured it out eventually Another noticeable challenge we encountered was syncing the google cloud data into our project so two users could communicate with one another

Accomplishments that we're proud of

We are proud of fully developing a set of models running with high confidence Syncing the database for communication amongst users Team work methodology in conquering and dividing tasks