User Guide for Review
User Guide for Study A - Z
User Guide for Quiz
View for Splash Screen
Siyuan: Being a person who identified as a Hard of Hearing student in UW-Madison, I was aware that many people did have stereotypes against Deaf or Hard of Hearing(DHOH) people. Many people consider the DHOH community as an isolated community and they hope DHOH people could communicate with hearing people by spoke language. However, in Deaf culture, many DHOH people really enjoy communicating with others and they love to use American Sign Language (ASL) to engage in communication. Therefore, I want to use a mobile app to help people who are interested in ASL to improve their fingerspelling skills.
Harry: As a person grow up with a cochlear implant, I can feel the world with sound or not. It's a very special experience and I want people to learn more about this special group. A mobile app would be a perfect platform to learn some interesting facts about the deafness, so I took Siyuan's invitation immediately when she asked me to join.
Yuren: Actually, I did not meet many DHOH people before I came to Madison for undergraduate study. After I came here, I met and made friends with different people within the DHOH community. The more I get in touch with this community, the more I want to learn about it. Therefore, when Siyuan asked me whether I wanted to join her for this project, I joined without hesitation.
What it does
WiSign is divided into two main functions, Quiz and Study
This function test how the user learns the fingerspelling in ASL. We fulfill this aim by testing how users identify different words by fingerspelling, combinations of signed alphabets, in different length-of-word ranges and send the words they inaccurately identify to review words list.
Users can choose one of the four modes: easy, normal, hard, and evil, which contains words with length less than 3 characters, 4 - 6 characters, 7 - 8 characters, and equal or over 9 characters, separately.
Our word list is generated from dictionaries in the Github repository and can be found from https://github.com/stoneotaku/vobmaster.git. We developed a python program to filter all the words in the word lists to the length corresponding to the 4 modes.
Every word is shown to the users by images of ASL alphabet signs corresponding to characters in the words. The duration of each image is 0.5 seconds.
We check how the user learns the fingerspelling in ASL by asking them to type the words they see and check whether they identify each sign accurately. The test input is not case sensitive. If the user enters the correct answer, the app will swift to the next question automatically. Otherwise, the current question will be added to the review words list and the images will be displayed again for users. The users can also put the current question directly to the review words list and see the answer directly. Users can take as many quizzes as they want.
The study section has two parts, Study A - Z and Review.
Study A - Z part is designed for new ASL learners. They can view all the characters in alphabet order individually.
Review part is designed for users to go over words they identified inaccurately or put into review words list during the quizzes. In this part, the images of signs are displayed the same as that in the quiz. However, users are not required to enter the words; instead, they can click the button to see answers directly. Besides, they can choose to remove the words from the review words list if they believe they master this combination of signs. After the user clicks the remove button, the button will change to the button for putting the words back if users remove them mistakenly.
How we built it
We used Github to work as a team and achieve the goal of version control. Each one of us has a task: Siyuan is responsible for UI of the app, Yuren is responsible for the icon design, string generator and image player, Harry is responsible for icon design, link images to string and view management. We started with simple tasks and tried to add features to our app after debugging the basic version. We always make a plot graph before moving on the next objective. Therefore, we communicate effectively and maximized our learning experience in 24 hours.
Challenges we ran into
We had a lot trouble with Github at first. Sometimes Github can't resolve the conflicts when two person modified same file at the same time . We solved the problem by always asking other teammates what changes they have made before update their own versions to GitHub. It's our first time to program in Swift, so we had to learn everything from scratch and develop this program in 24 hours. We had a lot of difficult times trying to create objects, connecting code with UI design, and switching from different view controller to maintain a good functionalities for our app.
Accomplishments that we're proud of
We are totally new to Swift and iOS app development and we developed the app by ourselves in only 24 hours. Also, we designed fantastic icons for our app in representing love and badger pride.
What we learned
Swift, UI Design, UIKit
What's next for WiSign
- The current image speed is set to 0.5 seconds, we hope to update the setting and enable users to set the different speed according to their ability with fingerspelling in ASL.
- The current UI is only compatible with iPhone XR. We hope to improve the UI and adapt it to all the currently available devices.
- We believe that daily practice is important than Setting daily goals for the user based on their quiz results. We want to include motivations for users to do so. To do so, we may add sections such as daily challenges, rankings, and archives.
- We believe it is also of great importance for users to use the actual signs in ASL in addition to identifying longer phase and sentence. Therefore, we hope to use a large number of videos to train models to recognize fingers' and palms' movements by users. In this way, we are able to test whether users can use the actual signs in ASL corresponding to the phrases or even sentences.
- We want to help connect and enlarge the Deaf Community as well as spreading its culture. We hope to build an online cloud community within WiSign so that ASL users and learners across the world can get in touch with each other better.